{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.integrate import odeint\n",
    "import numpy as np\n",
    "import theano \n",
    "from theano import *\n",
    "import matplotlib.pyplot as plt\n",
    "import pymc3 as pm\n",
    "\n",
    "THEANO_FLAGS='optimizer=fast_compile'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lotka-Volterra with manual gradients\n",
    "\n",
    "by [Sanmitra Ghosh](https://www.mrc-bsu.cam.ac.uk/people/in-alphabetical-order/a-to-g/sanmitra-ghosh/)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mathematical models are used ubiquitously in a variety of science and engineering domains to model the time evolution of physical variables. These mathematical models are often described as ODEs that are characterised by model structure - the functions of the dynamical variables - and model parameters. However, for the vast majority of systems of practical interest it is necessary to infer both the model parameters and an appropriate model structure from experimental observations. This experimental data often appears to be scarce and incomplete. Furthermore, a large variety of models described as dynamical systems show traits of sloppiness (see [Gutenkunst et al., 2007](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.0030189)) and have unidentifiable parameter combinations. The task of inferring model parameters and structure from experimental data is of paramount importance to reliably analyse the behaviour of dynamical systems and draw faithful predictions in light of the difficulties posit by their complexities. Moreover, any future model prediction should encompass and propagate variability and uncertainty in model parameters and/or structure. Thus, it is also important that the inference methods are equipped to quantify and propagate the aforementioned uncertainties from the model descriptions to model predictions. As a natural choice to handle uncertainty, at least in the parameters, Bayesian inference is increasingly used to fit ODE models to experimental data ([Mark Girolami, 2008](https://www.sciencedirect.com/science/article/pii/S030439750800501X)). However, due to some of the difficulties that I pointed above, fitting an ODE model using Bayesian inference is a challenging task. In this tutorial I am going to take up that challenge and will show how PyMC3 could be potentially used for this purpose. \n",
    "\n",
    "I must point out that model fitting (inference of the unknown parameters) is just one of many crucial tasks that a modeller has to complete in order to gain a deeper understanding of a physical process. However, success in this task is crucial and this is where PyMC3, and probabilistic programming (ppl) in general, is extremely useful. The modeller can take full advantage of the variety of samplers and distributions provided by PyMC3 to automate inference.\n",
    "\n",
    "In this tutorial I will focus on the fitting exercise, that is estimating the posterior distribution of the parameters given some noisy experimental time series. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bayesian inference of the parameters of an ODE\n",
    "\n",
    "I begin by first introducing the Bayesian framework for inference in a coupled non-linear ODE defined as \n",
    "$$\n",
    "\\frac{d X(t)}{dt}=\\boldsymbol{f}\\big(X(t),\\boldsymbol{\\theta}\\big),\n",
    "$$\n",
    "where $X(t)\\in\\mathbb{R}^K$ is the solution, at each time point, of the system composed of $K$ coupled ODEs - the state vector - and $\\boldsymbol{\\theta}\\in\\mathbb{R}^D$ is the parameter vector that we wish to infer. $\\boldsymbol{f}(\\cdot)$ is a non-linear function that describes the governing dynamics. Also, in case of an initial value problem, let the matrix $\\boldsymbol{X}(\\boldsymbol{\\theta}, \\mathbf{x_0})$ denote the solution of the above system of equations at some specified time points for the parameters $\\boldsymbol{\\theta}$ and initial conditions $\\mathbf{x_0}$.\n",
    "\n",
    "Consider a set of noisy experimental observations $\\boldsymbol{Y} \\in \\mathbb{R}^{T\\times K}$ observed at $T$ experimental time points for the $K$ states. We can obtain the likelihood $p(\\boldsymbol{Y}|\\boldsymbol{X})$, where I use the symbol $\\boldsymbol{X}:=\\boldsymbol{X}(\\boldsymbol{\\theta}, \\mathbf{x_0})$,  and combine that with a prior distribution $p(\\boldsymbol{\\theta})$ on the parameters, using the Bayes theorem, to obtain the posterior distribution as\n",
    "$$\n",
    "p(\\boldsymbol{\\theta}|\\boldsymbol{Y})=\\frac{1}{Z}p(\\boldsymbol{Y}|\\boldsymbol{X})p(\\boldsymbol{\\theta}),\n",
    "$$\n",
    "where $Z=\\int p(\\boldsymbol{Y}|\\boldsymbol{X})p(\\boldsymbol{\\theta}) d\\boldsymbol{\\theta} $ is the intractable marginal likelihood. Due to this intractability we resort to approximate inference and apply MCMC. \n",
    "\n",
    "For this tutorial I have chosen two ODEs: \n",
    "1. The [__Lotka-Volterra predator prey model__ ](http://www.scholarpedia.org/article/Predator-prey_model)\n",
    "2. The [__Fitzhugh-Nagumo action potential model__](http://www.scholarpedia.org/article/FitzHugh-Nagumo_model)\n",
    "\n",
    "I will showcase two distinctive approaches (__NUTS__ and __SMC__ step methods), supported by PyMC3, for the estimation of unknown parameters in these models. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lotka-Volterra predator prey model\n",
    "\n",
    " The Lotka Volterra model depicts an ecological system that is used to describe the interaction between a predator and prey species. This ODE given by\n",
    " $$\n",
    " \\begin{aligned}\n",
    " \t\\frac{d x}{dt} &=\\alpha x -\\beta xy \\\\\n",
    " \t\\frac{d y}{dt} &=-\\gamma y + \\delta xy,\n",
    " \\end{aligned}\n",
    " $$\n",
    " shows limit cycle behaviour and has often been used for benchmarking Bayesian inference methods. $\\boldsymbol{\\theta}=(\\alpha,\\beta,\\gamma,\\delta, x(0),y(0))$ is the set of unknown parameters that we wish to infer from experimental observations of the state vector $X(t)=(x(t),y(t))$ comprising the concentrations of the prey and the predator species respectively. $x(0), y(0)$ are the initial values of the states needed to solve the ODE, which are also treated as unknown quantities. The predator prey model was recently used to demonstrate the applicability of the NUTS sampler, and the Stan ppl in general, for inference in ODE models. I will closely follow [this](https://mc-stan.org/users/documentation/case-studies/lotka-volterra-predator-prey.html) Stan tutorial and thus I will setup this model and associated inference problem (including the data) exactly as was done for the Stan tutorial. Let me first write down the code to solve this ODE using the SciPy's `odeint`. Note that the methods in this tutorial is not limited or tied to `odeint`. Here I have chosen `odeint` to simply stay within PyMC3's dependencies (SciPy in this case). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class LotkaVolterraModel(object):  \n",
    "    def __init__(self, y0=None):\n",
    "        self._y0 = y0\n",
    "\n",
    "    def simulate(self, parameters, times): \n",
    "        alpha, beta, gamma, delta, Xt0, Yt0 = [x for x in parameters]\n",
    "        def rhs(y, t, p):\n",
    "            X, Y = y\n",
    "            dX_dt = alpha*X - beta*X*Y\n",
    "            dY_dt = -gamma*Y + delta*X*Y\n",
    "            return dX_dt, dY_dt\n",
    "\n",
    "        values = odeint(rhs, [Xt0, Yt0], times, (parameters,))\n",
    "        return values        \n",
    "ode_model = LotkaVolterraModel()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Handling ODE gradients\n",
    "\n",
    "NUTS requires the gradient of the log of the target density w.r.t. the unknown parameters, $\\nabla_{\\boldsymbol{\\theta}}p(\\boldsymbol{\\theta}|\\boldsymbol{Y})$, which can be evaluated using the chain rule of differentiation as \n",
    "$$ \\nabla_{\\boldsymbol{\\theta}}p(\\boldsymbol{\\theta}|\\boldsymbol{Y}) = \\frac{\\partial p(\\boldsymbol{\\theta}|\\boldsymbol{Y})}{\\partial \\boldsymbol{X}}^T \\frac{\\partial \\boldsymbol{X}}{\\partial \\boldsymbol{\\theta}}.$$\n",
    "\n",
    "The gradient of an ODE w.r.t. its parameters, the term $\\frac{\\partial \\boldsymbol{X}}{\\partial \\boldsymbol{\\theta}}$, can be obtained using local sensitivity analysis, although this is not the only method to obtain gradients. However, just like solving an ODE (a non-linear one to be precise) evaluation of the gradients can only be carried out using some sort of numerical method, say for example the famous Runge-Kutta method for non-stiff ODEs. PyMC3 uses Theano as the automatic differentiation engine and thus all models are implemented by stitching together available primitive operations (Ops) supported by Theano. Even to extend PyMC3 we need to compose models that can be expressed as symbolic combinations of Theano's Ops. However, if we take a step back and think about Theano then it is apparent that neither the ODE solution nor its gradient w.r.t. to the parameters can be expressed symbolically as combinations of Theano’s primitive Ops. Hence, from Theano’s perspective an ODE (and for that matter any other form of a non-linear differential equation) is a non-differentiable black-box function. However, one might argue that if a numerical method is coded up in Theano (using say the `scan` Op), then it is possible to symbolically express the numerical method that evaluates the ODE states, and then we can easily use Theano’s automatic differentiation engine to obtain the gradients as well by differentiating through the numerical solver itself. I like to point out that the former, obtaining the solution, is indeed possible this way but the obtained gradient would be error-prone. Additionally, this entails to a complete ‘re-inventing the wheel’ as one would have to implement decades old sophisticated numerical algorithms again from scratch in Theano. \n",
    "\n",
    "Thus, in this tutorial I am going to present the alternative approach which consists of defining new [custom Theano Ops](http://deeplearning.net/software/theano_versions/dev/extending/extending_theano.html), extending Theano, that will wrap both the numerical solution and the vector-Matrix product, $ \\frac{\\partial p(\\boldsymbol{\\theta}|\\boldsymbol{Y})}{\\partial \\boldsymbol{X}}^T \\frac{\\partial \\boldsymbol{X}}{\\partial \\boldsymbol{\\theta}}$, often known as the _**vector-Jacobian product**_ (VJP) in automatic differentiation literature. I like to point out here that in the context of non-linear ODEs the term Jacobian is used to denote gradients of the ODE dynamics $\\boldsymbol{f}$ w.r.t. the ODE states $X(t)$. Thus, to avoid confusion, from now on I will use the term _**vector-sensitivity product**_ (VSP) to denote the same quantity that the term VJP denotes.\n",
    "\n",
    "I will start by introducing the forward sensitivity analysis.\n",
    "\n",
    "## ODE sensitivity analysis\n",
    "\n",
    "For a coupled ODE system $\\frac{d X(t)}{dt} = \\boldsymbol{f}(X(t),\\boldsymbol{\\theta})$, the local sensitivity of the solution to a parameter is defined by how much the solution would change by changes in the parameter, i.e. the sensitivity of the the $k$-th state is simply put the time evolution of its graident w.r.t. the $d$-th parameter. This quantitiy, denoted as $Z_{kd}(t)$, is given by\n",
    "$$Z_{kd}(t)=\\frac{d }{d t} \\left\\{\\frac{\\partial X_k (t)}{\\partial \\theta_d}\\right\\} = \\sum_{i=1}^K \\frac{\\partial f_k}{\\partial X_i (t)}\\frac{\\partial X_i (t)}{\\partial \\theta_d} + \\frac{\\partial f_k}{\\partial \\theta_d}.$$\n",
    "\n",
    "Using forward sensitivity analysis we can obtain both the state $X(t)$ and its derivative w.r.t the parameters, at each time point, as the solution to an initial value problem by augmenting the original ODE system with the sensitivity equations $Z_{kd}$. The augmented ODE system $\\big(X(t), Z(t)\\big)$ can then be solved together using a chosen numerical method. The augmented ODE system needs the initial values for the sensitivity equations. All of these should be set to zero except the ones where the sensitivity of a state w.r.t. its own initial value is sought, that is $  \\frac{\\partial X_k(t)}{\\partial X_k (0)} =1 $. Note that in order to solve this augmented system we have to embark in the tedious process of deriving $ \\frac{\\partial f_k}{\\partial X_i (t)}$, also known as the Jacobian of an ODE, and $\\frac{\\partial f_k}{\\partial \\theta_d}$ terms. Thankfully, many ODE solvers calculate these terms and solve the augmented system when asked for by the user. An example would be the [SUNDIAL CVODES solver suite](https://computation.llnl.gov/projects/sundials/cvodes). A Python wrapper for CVODES can be found [here](https://jmodelica.org/assimulo/). \n",
    "\n",
    "However, for this tutorial I would go ahead and derive the terms mentioned above, manually, and solve the Lotka-Volterra ODEs alongwith the sensitivites in the following code block. The functions `jac` and `dfdp` below calculate $ \\frac{\\partial f_k}{\\partial X_i (t)}$ and $\\frac{\\partial f_k}{\\partial \\theta_d}$ respectively for the Lotka-Volterra model. For conveniance I have transformed the sensitivity equation in a matrix form. Here I extended the solver code snippet above to include sensitivities when asked for."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_states = 2\n",
    "n_odeparams = 4\n",
    "n_ivs = 2\n",
    "\n",
    "class LotkaVolterraModel(object):  \n",
    "    def __init__(self, n_states, n_odeparams, n_ivs, y0=None):\n",
    "        self._n_states = n_states\n",
    "        self._n_odeparams = n_odeparams\n",
    "        self._n_ivs = n_ivs\n",
    "        self._y0 = y0\n",
    "    def simulate(self, parameters, times):\n",
    "        return self._simulate(parameters, times, False)\n",
    "    def simulate_with_sensitivities(self, parameters, times):\n",
    "        return self._simulate(parameters, times, True)\n",
    "    def _simulate(self, parameters, times, sensitivities): \n",
    "        alpha, beta, gamma, delta, Xt0, Yt0 = [x for x in parameters]\n",
    "        def r(y, t, p):\n",
    "            X, Y = y\n",
    "            dX_dt = alpha*X - beta*X*Y\n",
    "            dY_dt = -gamma*Y + delta*X*Y\n",
    "            return dX_dt, dY_dt\n",
    "        if sensitivities:\n",
    "            def jac(y):\n",
    "                X, Y = y\n",
    "                ret = np.zeros((self._n_states, self._n_states))\n",
    "                ret[0, 0] = alpha - beta*Y\n",
    "                ret[0, 1] = - beta*X\n",
    "                ret[1, 0] = delta*Y\n",
    "                ret[1, 1] = -gamma + delta*X\n",
    "                return ret\n",
    "            def dfdp(y):\n",
    "                X, Y = y\n",
    "                ret = np.zeros((self._n_states, \n",
    "                                self._n_odeparams + self._n_ivs)) # except the following entries\n",
    "                ret[0, 0] = X      # \\frac{\\partial  [\\alpha X - \\beta XY]}{\\partial \\alpha}, and so on...\n",
    "                ret[0, 1] = - X*Y\n",
    "                ret[1, 2] = -Y\n",
    "                ret[1, 3] = X*Y \n",
    "\n",
    "                return ret\n",
    "            def rhs(y_and_dydp, t, p):\n",
    "                y = y_and_dydp[0:self._n_states]\n",
    "                dydp = y_and_dydp[self._n_states:].reshape((self._n_states, \n",
    "                                                            self._n_odeparams + self._n_ivs))\n",
    "                dydt = r(y, t, p)\n",
    "                d_dydp_dt = np.matmul(jac(y), dydp) + dfdp(y)\n",
    "                return np.concatenate((dydt, d_dydp_dt.reshape(-1)))\n",
    "            y0 = np.zeros( (2*(n_odeparams+n_ivs)) + n_states )\n",
    "            y0[6] = 1.            #\\frac{\\partial  [X]}{\\partial Xt0} at t==0, and same below for Y\n",
    "            y0[13] = 1.         \n",
    "            y0[0:n_states] = [Xt0, Yt0]\n",
    "            result = odeint(rhs, y0, times, (parameters,),rtol=1e-6,atol=1e-5)\n",
    "            values = result[:, 0:self._n_states]\n",
    "            dvalues_dp = result[:, self._n_states:].reshape((len(times), \n",
    "                                                             self._n_states, \n",
    "                                                             self._n_odeparams + self._n_ivs))\n",
    "            return values, dvalues_dp\n",
    "        else:\n",
    "            values = odeint(r, [Xt0, Yt0], times, (parameters,),rtol=1e-6,atol=1e-5)\n",
    "            return values        \n",
    "ode_model = LotkaVolterraModel(n_states, n_odeparams, n_ivs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this model I have set the relative and absolute tolerances to $10^{-6}$ and $10^{-5}$ respectively, as was suggested in the Stan tutorial. This will produce sufficiently accurate solutions. Further reducing the tolerances will increase accuracy but at the cost of increasing the computational time. A thorough discussion on the choice and use of a numerical method for solving the ODE is out of the scope of this tutorial. However, I must point out that the inaccuracies of the ODE solver do affect the likelihood and as a result the inference. This is more so the case for stiff systems. I would recommend interested readers to this nice blog article where this effect is discussed thoroughly for a [cardiac ODE model](https://mirams.wordpress.com/2018/10/17/ode-errors-and-optimisation/). There is also an emerging area of uncertainty quantification that attacks the problem of noise arisng from impreciseness of numerical algorithms, [probabilistic numerics](http://probabilistic-numerics.org/). This is indeed an elegant framework to carry out inference while taking into account the errors coming from the numeric ODE solvers.\n",
    "\n",
    "## Custom ODE Op\n",
    "\n",
    "In order to define the custom `Op` I have written down two `theano.Op` classes `ODEGradop`, `ODEop`. `ODEop` essentially wraps the ODE solution and will be called by PyMC3. The `ODEGradop` wraps the numerical VSP and this op is then in turn used inside the `grad` method in the `ODEop` to return the VSP. Note that we pass in two functions: `state`, `numpy_vsp` as arguments to respective Ops. I will define these functions later. These functions act as shims using which we connect the python code for numerical solution of sate and VSP to Theano and thus PyMC3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "class ODEGradop(theano.Op):\n",
    "    def __init__(self, numpy_vsp):\n",
    "        self._numpy_vsp = numpy_vsp\n",
    "\n",
    "    def make_node(self, x, g):\n",
    "        x = theano.tensor.as_tensor_variable(x)\n",
    "        g = theano.tensor.as_tensor_variable(g)\n",
    "        node = theano.Apply(self, [x, g], [g.type()])\n",
    "        return node\n",
    "\n",
    "    def perform(self, node, inputs_storage, output_storage):\n",
    "        x = inputs_storage[0]\n",
    "\n",
    "        g = inputs_storage[1]\n",
    "        out = output_storage[0]\n",
    "        out[0] = self._numpy_vsp(x, g)       # get the numerical VSP\n",
    "        \n",
    "class ODEop(theano.Op):\n",
    "\n",
    "    def __init__(self, state, numpy_vsp):\n",
    "        self._state = state\n",
    "        self._numpy_vsp = numpy_vsp\n",
    "\n",
    "    def make_node(self, x):\n",
    "        x = theano.tensor.as_tensor_variable(x)\n",
    "\n",
    "        return theano.Apply(self, [x], [x.type()])\n",
    "\n",
    "    def perform(self, node, inputs_storage, output_storage):\n",
    "        x = inputs_storage[0]\n",
    "        out = output_storage[0]\n",
    "        \n",
    "        out[0] = self._state(x)               # get the numerical solution of ODE states\n",
    "\n",
    "    def grad(self, inputs, output_grads):\n",
    "        x = inputs[0]\n",
    "        g = output_grads[0]\n",
    "\n",
    "        grad_op = ODEGradop(self._numpy_vsp)  # pass the VSP when asked for gradient \n",
    "        grad_op_apply = grad_op(x, g)\n",
    "        \n",
    "        return [grad_op_apply]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I must point out that the way I have defined the custom ODE Ops above there is the possibility that the ODE is solved twice for the same parameter values, once for the states and another time for the VSP. To avoid this behaviour I have written a helper class which stops this double evaluation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class solveCached(object):\n",
    "    def __init__(self, times, n_params, n_outputs):\n",
    "      \n",
    "        self._times = times\n",
    "        self._n_params = n_params\n",
    "        self._n_outputs = n_outputs\n",
    "        self._cachedParam = np.zeros(n_params)\n",
    "        self._cachedSens = np.zeros((len(times), n_outputs, n_params))\n",
    "        self._cachedState = np.zeros((len(times),n_outputs))\n",
    "        \n",
    "    def __call__(self, x):\n",
    "        \n",
    "        if np.all(x==self._cachedParam):\n",
    "            state, sens = self._cachedState, self._cachedSens\n",
    "            \n",
    "        else:\n",
    "            state, sens = ode_model.simulate_with_sensitivities(x, times)\n",
    "        \n",
    "        return state, sens\n",
    "times = np.arange(0, 21) # number of measurement points (see below)   \n",
    "cached_solver=solveCached(times, n_odeparams + n_ivs, n_states)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The ODE state & VSP evaluation\n",
    "\n",
    "Most ODE systems of practical interest will have multiple states and thus the output of the solver, which I have denoted so far as $\\boldsymbol{X}$, for a system with $K$ states solved on $T$ time points, would be a $T \\times K$-dimensional matrix. For the Lotka-Volterra model the columns of this matrix represent the time evolution of the individual species concentrations. I flatten this matrix to a $TK$-dimensional vector $vec(\\boldsymbol{X})$, and also rearrange the sensitivities accordingly to obtain the desired vector-matrix product. It is beneficial at this point to test the custom Op as described [here](http://deeplearning.net/software/theano_versions/dev/extending/extending_theano.html#how-to-test-it)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def state(x):\n",
    "    State, Sens = cached_solver(np.array(x,dtype=np.float64))\n",
    "    cached_solver._cachedState, cached_solver._cachedSens, cached_solver._cachedParam = State, Sens, x\n",
    "    return State.reshape((2*len(State),))\n",
    "\n",
    "def numpy_vsp(x, g):    \n",
    "    numpy_sens = cached_solver(np.array(x,dtype=np.float64))[1].reshape((n_states*len(times),len(x)))\n",
    "    return numpy_sens.T.dot(g)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The  Hudson's Bay Company data\n",
    "\n",
    "The Lotka-Volterra predator prey model has been used previously to successfully explain the dynamics of natural populations of predators and prey, such as the lynx and snowshoe hare data of the Hudson's Bay Company. This is the same data (that was shared [here](https://github.com/stan-dev/example-models/tree/master/knitr/lotka-volterra)) used in the Stan example and thus I will use this data-set as the experimental observations $\\boldsymbol{Y}(t)$ to infer the parameters. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x540 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Year = np.arange(1900,1921,1)\n",
    "Lynx = np.array([4.0, 6.1, 9.8, 35.2, 59.4, 41.7, 19.0, 13.0, 8.3, 9.1, 7.4,\n",
    "                8.0, 12.3, 19.5, 45.7, 51.1, 29.7, 15.8, 9.7, 10.1, 8.6])\n",
    "Hare = np.array([30.0, 47.2, 70.2, 77.4, 36.3, 20.6, 18.1, 21.4, 22.0, 25.4, \n",
    "                 27.1, 40.3, 57.0, 76.6, 52.3, 19.5, 11.2, 7.6, 14.6, 16.2, 24.7])\n",
    "plt.figure(figsize=(15, 7.5))\n",
    "plt.plot(Year,Lynx,color='b', lw=4, label='Lynx')\n",
    "plt.plot(Year,Hare,color='g', lw=4, label='Hare')\n",
    "plt.legend(fontsize=15)\n",
    "plt.xlim([1900,1920])\n",
    "plt.xlabel('Year', fontsize=15)\n",
    "plt.ylabel('Concentrations', fontsize=15)\n",
    "plt.xticks(Year,rotation=45)\n",
    "plt.title('Lynx (predator) - Hare (prey): oscillatory dynamics', fontsize=25);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The probablistic model\n",
    "\n",
    "I have now got all the ingredients needed in order to define the probabilistic model in PyMC3. As I have mentioned previously I will set up the probabilistic model with the exact same likelihood and priors used in the Stan example. The observed data is defined as follows:\n",
    "\n",
    "$$\\log (\\boldsymbol{Y(t)}) = \\log (\\boldsymbol{X(t)}) + \\eta(t),$$ \n",
    "\n",
    "where $\\eta(t)$ is assumed to be zero mean i.i.d Gaussian noise with an unknown standard deviation $\\sigma$, that needs to be estimated. The above multiplicative (on the natural scale) noise model encodes a lognormal distribution as the likelihood:\n",
    "\n",
    "$$\\boldsymbol{Y(t)} \\sim \\mathcal{L}\\mathcal{N}(\\log (\\boldsymbol{X(t)}), \\sigma^2).$$\n",
    "\n",
    "The following priors are then placed on the parameters:\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "x(0), y(0) &\\sim  \\mathcal{L}\\mathcal{N}(\\log(10),1),\\\\\n",
    "\\alpha, \\gamma &\\sim \\mathcal{N}(1,0.5),\\\\\n",
    "\\beta, \\delta &\\sim \\mathcal{N}(0.05,0.05),\\\\\n",
    "\\sigma &\\sim \\mathcal{L}\\mathcal{N}(-1,1).\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "For an intuitive explanation, which I am omitting for brevity, regarding the choice of priors as well as the likelihood model, I would recommend the Stan example mentioned above. The above probabilistic model is defined in PyMC3 below. Note that the flattened state vector is reshaped to match the data dimensionality.\n",
    "\n",
    "Finally, I use the `pm.sample` method to run NUTS by default and obtain $1500$ post warm-up samples from the posterior."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [sigma, yto, xto, delta, gamma, beta, alpha]\n",
      "Sampling 2 chains, 0 divergences:   2%|▏         | 94/5000 [01:02<59:45,  1.37draws/s]  /Users/demetri/anaconda3/envs/gsoc/lib/python3.6/site-packages/scipy/integrate/odepack.py:247: ODEintWarning: Excess work done on this call (perhaps wrong Dfun type). Run with full_output = 1 to get quantitative information.\n",
      "  warnings.warn(warning_msg, ODEintWarning)\n",
      "Sampling 2 chains, 0 divergences:   2%|▏         | 108/5000 [01:09<54:44,  1.49draws/s]  /Users/demetri/anaconda3/envs/gsoc/lib/python3.6/site-packages/scipy/integrate/odepack.py:247: ODEintWarning: Excess work done on this call (perhaps wrong Dfun type). Run with full_output = 1 to get quantitative information.\n",
      "  warnings.warn(warning_msg, ODEintWarning)\n",
      "Sampling 2 chains, 0 divergences: 100%|██████████| 5000/5000 [12:57<00:00,  4.16draws/s] \n",
      "The acceptance probability does not match the target. It is 0.6992852935132228, but should be close to 0.8. Try to increase the number of tuning steps.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "theano.config.exception_verbosity= 'high'\n",
    "theano.config.floatX = 'float64'\n",
    "\n",
    "\n",
    "# Define the data matrix\n",
    "Y = np.vstack((Hare,Lynx)).T\n",
    "\n",
    "# Now instantiate the theano custom ODE op\n",
    "my_ODEop = ODEop(state,numpy_vsp)\n",
    "\n",
    "# The probabilistic model\n",
    "with pm.Model() as LV_model:\n",
    "\n",
    "    # Priors for unknown model parameters\n",
    "    \n",
    "    alpha =  pm.Normal('alpha', mu=1, sd=0.5)\n",
    "    beta =  pm.Normal('beta', mu=0.05, sd=0.05)\n",
    "    gamma =  pm.Normal('gamma', mu=1, sd=0.5)\n",
    "    delta =  pm.Normal('delta', mu=0.05, sd=0.05)\n",
    "    \n",
    "    xt0 = pm.Lognormal('xto', mu=np.log(10), sd=1)\n",
    "    yt0 = pm.Lognormal('yto', mu=np.log(10), sd=1)\n",
    "    sigma = pm.Lognormal('sigma', mu=-1, sd=1, shape=2)\n",
    "\n",
    "    # Forward model\n",
    "    all_params = pm.math.stack([alpha,beta,gamma,delta,xt0,yt0],axis=0)\n",
    "    ode_sol = my_ODEop(all_params)\n",
    "    forward = ode_sol.reshape(Y.shape)\n",
    "\n",
    "    # Likelihood \n",
    "    Y_obs = pm.Lognormal('Y_obs', mu=pm.math.log(forward), sd=sigma, observed=Y)\n",
    "    \n",
    "    trace = pm.sample(1500, tune=1000, init='adapt_diag')\n",
    "trace['diverging'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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mW5L94lBLzc+XLC/0N8z+NFrf32IpxkAzHDxW/gJu/giFxedyeeZfaDv2TL70htOnW6qDwrWvOYV/vPJ07lzfyye3nUf5Iw9A81y44W3w6H9NexiLwWA4MvBtATl1EZQzwdDLj7C49xES1gvrRegfL7C+a4z1XWP+iz1rDqnFtw1dYzy6LXrlv+rOTrU2XSkCkMgPR89nmBirrH5OtzE/SWbCx8b+cN+mXu7d2Dtl47nXoSGZ4NY1XWzvG6/rOGOgGQ4Oq66HO/4W6+TLeW/+78klZ/OD953nxbsfjlzzypP45ze/mHs39nHtQyXKH30Qzno3PPzvcNP7oZCebhENBsNM4mDkoDkqsJBy6spc25PPu5hyhnaRqmRpzXW9oGFy7tpaqTIFi2zT5EnYOZBhNBdt2L5QXlZZ9cuB0z2an3Thhf1BSknlBZgnat4NXWPkCjlGcyWGCofmQu8h5kCL5EDyecNvsU099emCh6+2bJg+1t8Mt38OTrmCf2n5Ms/3lvjOu85m2dyW6ZbsoHP1xSd4Rtpnb9lG+S3Xwev/E7bdAz+7DAa2TbeIBoNhxnAwQxyDHrTdg1kGM8X9G3QmGGiNqgR8wi5hTXFu3Vi+HGv0OT1mo23p0iQLlhTSM86tEC/OFMs5xcNlihVW7B7m+b2j6oVSDrrXTPn1LZQtblvbzZ3re6Z03Fgy/UqHyo+QLlTYOZDh+Y4Bdgxk2DGQf2FkmCJqLhCN7oXyAZ6PjA5DnBTFcdh6D5RrVzF1z6SpMAjFzKSmcK/DZBdDjIFmmFr2Pgt//gQcfzG3n/5/uXFFDx9/1Ym85vRDo4T+VHD1xSfw1Te+iLvW9/K536+l8tJr4EO3qfCEn74Gttw53SIaDIbDFFcHUB40n7Wdozy5YxJ5UzpuiFWdDGdLB6GCpGsp2VPaSqBYsXhkaz+PxIQAukQqm5Otdpgbgr6NkzvmIHPQzUUnZNIrsz9FM7pGetatqte5AoZ2qGs8hehFaerx3PaOFXhoS9/+e3nHOtXP7JC3OGA7hoxMNOzfmNOMCIfN2hbsew46HtvvMVtyXSzrugeZH637mFypUn1fhnZAKQPb7oau1bHHusbVwsFn1YL7JHCnnOwjYQw0w9Qxuhdu+itoP4Zdl/2IL926nQuOn8cXrjhtuiV7wfnrS05UOWnrevj879dSOfYi+PijsPAU+N374OFvmLw0g+FI5yCGOIJU+T9Tkbeie9AmkDlTrPD49oFgztZUIJS6IpAHFpaXH1FVCp2KeO7HcDofY4S6umXklPshRz54Pyq2zabu9LS1RHihqypO+XTe425HTyClMgj2E70SarGOMNc1+0YYL1Tq2jdM2bJ5dNsAA+MFEMIrzy6chQAr2Rw8INMP2+7dv/PLDcPm270cQVALK7eu6WIs7r0wSWLvtbuhWF8uVhTN+X71S6E+Ay1dKHP/pj52DoQWVZKN6qdtwfCu2OOn4rmd7BDGQDNMDcUM/Pa9UClReOdv+MQfO2huSPL99517WOed1eKaV57El15/Oret7eYLf1iLNXsZXH03nPN+ePQ/VV7aAXxAGQwGQxVask+i4xFym+6LzT+qm4JmbE2gqbi5OqNTpOR5CN9SqttAi1oE69ukPF/ZAWe02mNNfQ+n4Hg9owW294+z7wXo7xYVGlp9KQ9OxpBrCB40O1R7PvIlzWDZ95xqZ7Cf6AZsPUbXpBT5TbfBnqe8P1UvOkn/uDKa3KFERYXf2WEPWvcapUPsjx6x56mqBZzuUeWpGxjfz1DoGKrrzkzdQ1Dv9XYXYKo+C10DbQL2a1Fo062w5S7vz8kuhhyZmrNharFt+NPHoX8TXPUL/umpEtv6x/nOu85mSfvhn3dWi09cehJffN1p/HlNN1+8eS1Wsgne+gN4w385eWmXw9DO6RbTYDAcbHo3RPRGPHg5aELaiNI4m3rTsRX86kYP5eterRTLGFyDZuo9M443Qcr6lfwpyFFxlctoB9p+nKMIql2ugVhPXp3yAEwu/0WnPgNtog37hztarlSp31s4vEt5iCKoVvrVC33pPPdt6qU/7eQUje1zBKgx59DO2HwoGfvHgVMpFygNd/rDh8Z3jQLbcjzY4b6JoqZ7d4LJnetTp4ESZkd/hvWdtb3k8emNL7y32C3y05gKmT1i/82gCT/jrDKUc6YPmmEaeep7sOUOuOLf+ePY6fx+ZSefuvRkLj3tqOmWbEbwqVefzOcvP5VbVnfxpT+uU8rFyz8OH/gTZHrhp6+GHQ9Ot5gGg+FgUSnBwBboePSgT6XrApNWDNLdypCsGlQzdEZ2Q61S97UMmilB1l8kJCL0qzddIF0o+7lR2lBRCpenAk9ViGPIsgh7S+KQUpIrVdhwAKGjkQaaM/NobuqLr8RRdy+prtXKO1TrvrhXzrmu6bx6NkdyIQ9uJcYrVMpB9/MBT1YA/fmo4367e9TjcdnaO866Li1Ez5YI1wgTws9dcnJARdX8tSrY1Ilm9MngpQywbzjHrWu6vP5gG7vH2DVY32JB9XD7KW8pV2VI1ztS2VJ7ugbao9sGuHNdT93XLnw/13eOcdva7rqONX3QDNPDvhXw0NfgxW9l+wnv56t/3sDLT5jP5157ynRLNqP4zGWn8NnLTuHmVZ18+Zb1agXxxFfBNY/AnGPg1++Ep74/4yp8GQyGKWD349GvH4wcNKn9Mtnh9zylDMlwaOAk5DyQRX2PbfdFVLzVykzUK0/I41C2bHb0Z9gW04eoloEyZS0LtBX7bX1+ue2JTqkyBcZTlNGgD5uPac57IOwZymHZNvoDMen8rLDnSN/kDasevCRq36pz7VkTN4L6UYmo4te7gVlDayPmcv+OL78fe7u6VkH38xTKVtX1Tu59gtZcp2/QeAV/LOdnjAftgD5H4o1fnc4RZRhNJj9tyr3oW+/yi6xNsl+f137EObvRXImKbdd8tnTC99M1Tt373zWa59FtA5HPg/GgGV54iuPwx4/CnKXkXv//+ORvnqetKcn333suqSM076wWn3vtKXz6NSdz08p9fOXPG5SRNm85fPQ+OP1NcN9XVajogZaeNRgMM4v8yMT7TBHeKjiS/S5DVA4l0tepxKh5nUP2K+yqBHufgWIaeteFZHAUrAMIcQwYBs54+lB2YVzlqGmIsKdtEvl40fiKZbqgty+oPVY93q10Nkdm+xMTlgzXqVKip8TCVvSnC2zsHqNzJI/U5J9077IIT2hVZUDn74Tz1Fddr1KMt8c1mKOe8YEtNI/v9f4MX5F1nWPcub4ncA3dX10DMVeqqMIbrkdvuAOGdrLr8ZuqRcn2a+citJ6G7vlrMpYL2ufKgXvQHtjUV9Mj1pBU13d/+s5V2VL7877JRleglbbk9rXdbOqu3VssPpR3gvMp5SA3XPU+aXR0XNczt3dI9arrTVe/9/b37hgt2rD/3PsVGN2L/Muf8NV79rFjIMN333MuR81pnvjYIxAhBJ+//FQ+eelJ/Pa5vXz1VsdIa5oF77oBXv1VWHcT/OL1fqldg8Fw6JNIxWw4MCXYsiVP7xzigU192pCuMifrUqY6R3I8vTNUmjysEO+HQrVftsvg1pqffWr1exIhjiHla8IV/b1Pq1xqLedOhg25Dt0bWq8c2n4xOS9Sqp5b22O8e/Xcy+eef54tWzepc4iaY4LXpsrjsa1vnFypQtm5TxU7aK5PWsnvWx/b6iHsQXO9TN7rjbPUz9lLa89Rx7mHr8+e4VzVoe6Zuq/1pYvOvsFFj3KhuiiMO0w4rFbIivNTm0h/nxxQiKM61mtXgGb8Du305nEX3bNFiz1D6lzmD66E/i2M5cq+AaqNmxrehojsoThJeYvjsOuR2M22lGzv38+CaxMZaFvvgp0PVS0KudfDDddta0oC6vpUTSEljcUhlnXeScKqf/HEGGiG/WP7/bD6V3DxZ/hD/zHcsrqLz7zmFC4+eeF0SzajEULwxdedxt+86iR+8+xePnfTGpW8KgS86ovwnt+qD8WfXBofE28wGA4t5h6nfs5bHnx9fxWr7ucZXX0Ld6zrpn+8EFCuXCVSSLuughKr9ozQPx5WGsKxXJMPfduvU6t5kFQr8VKSGN6pmj5PRMjQ1Ee/d1Mfm3uCY9iuaqzlK/kRo25CULUXblJ4HpvgsRVb8vzeUTb1pBnJVuf4uSv14Bc8iEXasPkOVYZ9AnQxDjiKcryPTO8ONvekWbF7xOshFvagTPqyDXdA7/ra+zj3xesdJicRCqsdX/VyjTH0bWGj03sfen8Hj40KWfWOEeo/z2DzWgjoc+hWYe3nwbZlxHs8/ljvdnU/rzzaQMq5sFt606zZp/LmWgp90LeBR7b188i20LOW7qKhfyPtY1uUqMFkz3hhrQqM9wZfiywU4/bXq/8eL+u8k9YedT7NuR5S5Wz90QGhaZZ23kXCKnj33Q2dtKVUizha8TcJzB7vAKCxVH/fNmOgGSZPbhhuvRYWvYgtp1/L/7l1AxefvIDPXGbyzupBCMGXXn+aV4L/YzesJOcqWKdfCX/9ADTNgevfBE9fZ/LSDIZDnNF8me394/WpErYNOx6IDekBYGgn6fHoFWM5gZadLUataIcHCRto9Skxli2pWNWhg/UTPOrJHYN+pTipDDSBTaJ3jbpGEw5XW+5tfeMBJdsrYx7hrZERv+3XWcZo7KWKXbN4RkXLC7x7Qw+gyqLndM+HO2ZuGCoFsp3rGS/45xJlbATOfz8ttPFCWT1Xux8n0bVSjRUykGpdtbrmdXLEVu4eZuVuP+QsPINroO0eyoaKOMTMEWV4xxwVJ+WuwQx3re8hX7K0EMf4cepD+Hl0nrEXdw7xCyg9Y3k29aR5eucQwxGGf2QOWkR6V1JWWNJ9P02F4OdSrAHrvJ6wS8zruD1kZNUwertWUtn5WH0LMCF2DmS8IiZxpLLK+FswvJqj+h+re/EpbAgKadNcGPSeXc9zapUh08fW1Y+y1/GaSqmuA0BLvo96MQaaYfLc/feQGyT3ph/yyZs2Maelgf9+97kkE5NL2jySEULwiUtP4v++/Uwe3z7A+3/2rP/hedTpcM3DcNob4N4vqzy/Urb2gAaDYcaypWeMsXy5WnkY3gXrbw5WmCuNQ35UFROoQVVJbls6nhWlaLbkuiN3fmBzH4OZ6op2MrTCHVDmpA2JZE15KOVYd98NPLWpwx9PStj5cPU51slgpqjlxUgEygiREl+h3rcCdj4UPUBViGPt+TwDrZL3CqXIclEppZ4rrc4V9/yIMiKtsEEcneNVrNieQp6I0JArVrXwK3YP89i2akPeKqnwuVVdeR7aUtuLpo9qS+l73epocF4oW1i25KEt/TywWSmefg6kj4CQA8X/Y0f/OLev66ZYmUBRTqvnuWs0T9eon6cd9mymCiOkSrpyP5FpJEM/HVzva0R+WZjdg+p6lyp2VRVHv45HSMHXLpCv5DvbJpivamPPushd+scLPNcx7HnSI0NLazzPo7kSu51wxmQpTcIuMScdLN4TFnFLb5qHtvT5jeWlrQxLPQewxon19A+wpnOUlR01WoOManmB2lAbusZ4tmPi59ZFyP0vEuLeQFuq++dd23KekmUzXrS8Cq1tfSu8PMLWXCeNxVBIeQzGQDNMjs23w/o/IF/5Rb74pGD3UJbvvedcFs1umm7JDkne87LjuO6vzmNDd5q3/OAJtvY6q+LN7fCuG+Gyf1JNNn/2WtMvzWA4VAgpt22o1f98ucLW3nH60gXVMNVplhysICcolC2GsxEhSXufhd1PAtUK3+M7Brl7Q4+nsCTteIMoU6j2oknNkOhP53h8+wAdg87CkLRr5NE5pLuxKkVmZXarQ0Dlr+QcZaRYR0nuCSwoAaQq2eC5j+6JNyaqcukiptR+L1dspWh1rvSMvqbtd7Jw8FmE5VxPXaGzLVXYJIre9crQzg7ASId2EjEhjpbth7glgPG+QLEPq5BladfdpMrjzuFq32LFomLZ3Lqmi/YxlXsmHZkqDbMmOv2AGJaUkHFW+HMTK5H3buzlse1BRdodLiEEc1tVj61kQgQj8rTf9znVAQvlyeWlxT0pqbE9LO7X8gRDXqjqgWK2O82tgx606DFKlTLN+V6kVmHUM9C8ULx4ZOgXAbbcCiYAACAASURBVFApaJUHY4xIT4Do91Zs/ZeonaRk7sgGUuVxT+YdA5nIxRydsPdza+8444UKiISSNtIAir8abiPp2JBMCHjX3GuUrOSZN7yWXKHESLbEI1v7AwtigWuhV6mtM0LJqgQ/M9UjLbCk5Mmdg16VS5CO198ftzHTjRT+AlciMi+vGmOgGeqnMAZ3fREWn8kvxF9y57oevvi607nwpAXTLdkhzetfsoTff/xCShWbt1/3JPe7Cf+JBFzyd/D+P6qY7J9c6peYNRgMMw+rBJ2rsHc8yNaNzyuPlpReWFAmX2ZLb5p9Izl26PlheuEIIdjWN8623nFf+SnnVS7I2D4YV+FtYbXHVWzqUTiiFDWp9TbLly1mjXeQ2HCzMkKkDa53yTsgNE9SGXBuQQMpgX3PavtrElsV2HCL8orYtioCoHbydqlYNglLUw6lBASpSga7prqryxjyoE1w3IauUdZ2OjkihdHQMepntlhhR/+4UsA7V8DmmKbdrkI2vCtY+TGmSqJE0xulVK0ZtPYMMt2JkDZtWdV4WdeLS5YduB/eMGICryfBaxLurhCJbatzcuZLh8qu69ULlYIssW0Ze+3DJeUp5ZTHdQIPcviwOKwJPSTRI9hSUihbwa0xk80Z3siCoVVYWX+hwPMkxlTCD3jQvHBNzULrXV9tuQUG0X5vPzZSroZQNW1B1Bvf8TxWMrRl9zB/aHXk50PvWLTBZANH9T5Kcz7kqXU87iKqlmyNz6jWxtDnjOYti8QZa+7oBlpznSSyfTy2fYCxfJl7N/ZGH1OngaQvBFViitSs3D0ciDaQEc+6LUFqn/GyzubYxkAz1M9DX4fxXtaf/298496dvO6MxfzNq06cbqkOC845di63XfsKTjpqFtfcuJL/fmCbX6nspNfAxx+FBSfB794HD/5bZNlhg8EwzZSyMNLBcLbEYHeHKkIhfXNCximLofBCZYpI+txV5KEddVd2jZ4jFF4VoajZmgctgaR9bJNSUKxylQdtLF9i71A2EGo2lHfC8xzlp1ixGMhoSp206RrN89CWPmRxXI3Zt1Ep4tvurfJE2cCSHj3PTE7cl7dcCIYU1pFfUm+Kr7vf7sEMo/kyhZI2tvN5vK1vnH1OZT/P6LbDil30SUipKerutdA8I5YMGnZ6ny/1q25oRXtcos5VN8psKUnny34vJ9tSxtKw5gEc2KIaSIcVZ88To34UK3bQgzGBHFt606o6YM4J2XTmHMvHN0VPlTO0pXeqAaty0hSWGxo6sGVSUSg7+sfZ0D2GXuAi7lFpsNQ9t7VneChTQjp5kwCp/ABs/HPk8bJvY+Trboicn4OGumG7nwx6jesM04v2oDnFVZznVIYXYlC5pdlSTP8zCQ2VDG2O59xlvFihcyTnhDhGHBRDyinnf/ScZhUivO85b1vJsv2FKIdwnl50FzeCD51noAlPlpFciXWdowGPoH7Iyo5gKHEmNpe3+tyUyTZ5c8sYaIb66FwFz/2U7Dkf4er7LI5f0Mq3rjq7uheJYb85ur2Z33/8Qv7ynGX89wPb+cDPn/Xd/HOPg6vvgfM+CI9/G/73HZCtL47ZYDC8sEhdiZbx/h5/hVY30GzaWxoA6ZXoprEt4tjac9ci0oOmDZhw5ddkclfES5bN9v4Mz+9TxRpcVroV+6SvuHSPBg20VXtGGC9UNMeABLf3k10JGapVAnq5WZ4OFXb5bLmDobV3knYLYziGk5SSvnRh8lUKtfHd4isNofLagFdUZHNPmtV7nd5UroFW5cWKMZ7Q+ru5ir5mFHsemXAInVBhVgGx3dC4qIekXAj02tSfl+FsiW394/SMFVR5eter2rdBO9di4JxdGspjVeP5c0CymGbO2NbgBqtC++BqElaB3nTBqw7oMpgpsr0/w1CmyMB4IZBDJaXymswe2RzoMxieP+BB636+SrY4q9XtUWdLmJXpiN0V/PeT/khs7x/Xwt6gZWhjwHMTeAv2bw71rlNbq6uwSsj0Ki96uiv4egThMOio3EZvm2Og2YmGqvOs1dZixDGYBLYWJpnliR2DVGxJY8m/N2P5MhTSWKVCbHER9/4lpKVChDW29Y6zYyCDlDYy/FkwAVK6nwWo0vmAFIK+MfVc7R3OUbJsCuVowytVybKk+36gdpuIqGbwUsqA16yq4XgMxkAzTIxVgds/i5x9NNd0voFcyeLH7z+f2c3VKy2GA6O5Icm333U2//WOs1i9d4Qrv/s4j7sx/g3N8Jbvw5u/p0rw/+RV0V84BoMhgBDik0KIDiFEQQixSghxyQT7Nwoh/s05piiE2CuE+Ezd8yGQbhW2gKcj+OXt9lEKhKfZtgobk5Kcu0obEapWq3paJTUr/GJQvkgDzVcaEoE0KeccHAPNnTdVzrKs807lYRnvjVzFD0wj/Rwr6WwZzBQYzBTJFitVilGUou/WofKui1XtXeno7mOb20vMkalrNM8zu4b8nLp6kboHyDlvZ4U/oLRGyEEiydrOUTb1hpRs95kIhVnZUrunrtct0QAD2yDdgwzFArql9puy3Ty8uZfAPbaD+6L/ueWOQKi8/hi5XgG/MqRbs77iGWRS4rQBCI6drOSrxgOnqIuz9+zxHSAt/96O7qE5260KT8jqohzuOQ5lS+wZzvHYtmC+W6qSo2wHwzura33U1uAHM0VW7hkOGtyDfiEMiSRVyXi/R+G+n8JVOC1beovYolJg30jOW3QNvjeAsX3eaaQLQeM3sO+ep+gazQULDqW7I6u+1mW7OO8Rt1+ZLVJQDBpG9ug+z9iXQtCW2U2qnAnIKqQNhVEVJjm8Org4IARjeZUXNrD6Np5/7Fa2xvT7s+KeXfxG8wGjzAlFdvP0ZKwRWv35JEmwtXcs0Fw64JnW9m3LdnqVGD0iI0Yj5pFhz2R9VqUx0AwT8+z/QN96blp4LU92lvjmO8/mlMWzp1uqwxYhBO966bHcdu0rmNfayAd+/hxfu2OT/4F8/ofgI/eo33/+Olh94/QJazDMcIQQ7wa+C3wDOBd4CrhbCHFcjcN+B7weuAY4DbgKiC6VVoPOkTyW7oUJaa9eAr5m3GzpGaNkqcpn0aqCwtZCr3SkLbETDeRbjo6VK2olXS/Pn8Bt9ut4a2zfu+MqMC0FrVz07idISFep9McuWTZdo64RWn0ddvRn2DGQY3NvmifX7wycZ/Wp+S94IXjjqrLfaK4UXV67Z62zXcmmrnfIg6XrkVVT2loNBWdlv0oawCoHVtV39GewpKBs2Yxk8qEwPQm962Dr3aF5tPvteqmSKbq3PMvo5oe166F+eWhLP8s672TB8Gpmp3cEFOJ0sRK5kh+FvptbKVL16HL/oTyRm24F26ZztMDOwQy96XxgHLcoTfy0asOigWdp2eGcu0ggBLRl97Gs6x5acl2BI8IVEDO64SK9/5xnS6K94mHXSgdYfzO9m1W/0WDIatBAkqK6QI7eQ88NGQ4/g6othPO7XaYvXWDvcHWDaltKqBRrqO3eQ0ixYtEzVqj2rmmNnKsqRrrhixE3p2c0x56hLAIle2M5Tcvuh2Bwu7/T3mdoLPre8rmjGzmq7/HgQNL2vMapcobW0L10jSu3zYcXIhhXyCdCVs9TqW0TQztpKtSo+IgKPd7Vl3aG19/wTlSA1ldQL5ZUsVUvSb+SbEwen0akBy18HsaDZpgSRvfCw9+ga/Gl/MPm5XzskhN441lLpluqI4JTF8/mtmtfwQcvPJ6fP9HB2374JFt6nS+FZefBNY/C8RfBbdfCnX8X2bvHYDDweeB6KeVPpZSbpZSfBnqAT0TtLIS4ArgMuFJKeb+UcreU8lkp5SP1TijUQADctb7LV0bq+GLOubkeUkbkV+hIlnXdVRU2JpFIIagkW315wgpbpI7h7+P662wJm3rGeLZjkBV7xkAINnYH+xN1DGZI58vMGwk1Enbm7BkrKMU1wkDT52wfXBG7sPzUzkGQ0vNQeCN1rUZKyY6BjNqn6pTUnq4yW9QbPNdjwATCU53fvNAqGdhP96ht7B5j30jWO257f8b3+klZlb/VPrZZT3Ui0avWAsqJZrrH8uwYyHj3MCpsMWXl0S9e50hOhZM5+yYrOZASWdaMA2fhoFCxPC9P2bYpp2apc5G29wy6133d3gH/WoaMES+Hqerhkozny14+VWNpBKwC/ekCZRncVzXxdYyxYoXBjBs+5wldde5qimDoozdecQh7gsonhTG10JDS2wSFKpa64WlSwliuzO7BLNv6xlk48AzLOu8k6SxO6D3pXOKKhNhVVVFl4PnfFuFhEkgVeooq5FNFpUghl+G2td3sHcohJcxO72Bp930krAISFZ73yNZ+cs7xm7tHWbNvVHu+nBDksX2+rFJ6YZ7eft4iDv7fbml9bFpzfs6scP/ZleoG3XueDIR3uu+4KE+U14Q89DZeOOjnqS0YWsn8wZWB4zb3pCONInVfJRVLy5PL+6kjg5kSI7mSUwTEWaCJsZoai0PMGdsSWRTF9hY8vJmV4PnaTauNgWaIR0q48wtYEt7b+Q5ecfIi/v71p0+3VEcULY1J/u2tL+GXH34pg5kSb/nBk/z8iQ71hm9bAH91M1z0GVjxM7jhrZCpvZJkMBxJCCEagfOB+0Kb7gMuijnsbcAK4PNCiE4hxHYhxPeEEOG4wfpkqGEIeKuxrvJQKTGnW5XRT8iyp/wMZorsG6leeQcVNibskrZKbgMizgojVR6nac9jqlqehgx4+nwP2q7+DOAo6RF5FEPZUkyDZf+8y5ZN2EDz+qTFyKmvdA+MFylZlmcEVVUwJORdgSoPjzuvJ7/ncYlY8fZCDS3PIPE8aK6SGDisegz3krjXqeyXaIRkY2DfpuIQ2JLW8Z3qPjpVLcvCD4tqGoh34CqjKCiDlOocm3M9HN37MM2Ffhq2B712PWN5ukfz3rlVLBV8qgw0pVTuHMiwzqlsuWfIDxENl1cX0qZ/vIAtq+9nObRv2bJ5etcQa7vCzYiFp/Fv6U17vdHyjmEtwiGnzr6r91TnY6dKaRYNPINdqW/h0pOwUlLFawLbEt4+j2zr9yp9Njn9rBrL6jzClQ7VPagusz+WLwWLsyCRtkX3mP/MpgtllnXeydHdD2jWnaztfdl8O4VN6h53jeaRSJodT3eqkkdK9V4ayxXpGc1jS6kMKakbEML5U3qy2xISsnblQyFteseq33M6CbtcnTOW6Yft/sezuz3K0PHlcT7j0K+ra2Danne/NbtPtavAfx9KiRfVYCUaA3MCyEr0eXrXXbejnV8WDK5k0cAzzB7fGVntsurTQaLyDnc8ULWvjjHQDPFsuhW238v/s66iccHx/PCvzqsq22p4YXj16Udxz+cu4ZWnLOJrd2zig794Tn0QJFNwxdfg7T9T1dB+cqnJSzMYfBaiHEJ9odf7gLgYwBOBVwBnA+8ArkWFO14ftbMQ4hohxEohxMp0elwrO+4qqvEhjt6ivft6Maiw5oc66RnLs2bvEH3p8Be/rwgv7b6fpd33kazkHI+BCGxvKI8xf2gVSEn76GaShSEvd8OXrdq75P3vGVKa8q3tn9S8D5JqBb0SXkF2PE7KSNL3r/JXeViWr5wXyxYr9wwzki2xvksVp1jWqRkfqOT/WsxOb4/d5nrHCuWQcq8preHG3lV2uOf9DCmaEkhW52835ntpH91M+9gWRqwW0oVyYI7Ab1WTBb+XF7Y1OucgaSmoIixJx4OiCzKSVefXkuuiLbPbCR2VTgiZmmcs74fHteR7vPtrh85LSIu9wzlkVUhhlAGsfo4XIir8RRggbvhonHEyMJ73DB7fzHDzlerwlOpSRvUU8zxo0WPFpoOid1Xwd9renwkaIBJG8+VIr1jSLvp90GSwhHtfusDKPcN+yC9glZXXsTHlPKfeoortHTtvRBn7FVuSqmRpy+7RDBB/rMgm2zH3QEibVbujC5e5Hx1CVqIvlpbDaXtvG3+elXuG2ZybpRVjkdr+8fd33sg6rVWFP5676GInGp1r6mPbNslKloQV/vzwPxPdzxb3vjRr4d5xOWjqPycfEdsvjlQDo20boimMYd/192xPnMjveAO/+NBLncpihuli4awmfvrB8/mPt5/Jqj0jvP67j3H3etUTibOugo/cqz4Jf/F6WPf76RXWYDh0UXEv8D4ntPFelJH2DiHE4vDOUsqfSCkvkFJe0No2i239415lMwAR+PYPeR1c5S07oCrRhcKUE3aB5zqGaXCaE1dqVA8DpYSrFV4RMJQWDK6kJd9L0sr5oUnV5wHAQKbAmn1642d9JP+owIp6pI4kg78GiqVYzqUI+a9iij3MTm9HaCXS3RyUntgVe0nZluwZykYqTKBKg4enDIvxrBY2eVT3Q4HQxKBiKGMVRd9Q8PclkQr0D0tVsjR3qzCthF2iazTHtr7xQF6gez1ac10s67orKK8QgefMduQT0iZphTylWtisW/Bk/vAa5o5uZNGe20lVlJfMsuzA+Vq2ZO7oRj/EM8KDVn1d4mnL7GHu4Iq6DDQXvcHvo1rBECFtKlrFTsDrARcrTei5qCX33DntztjQVBjk6J4HQVqUGtprzhEwsEPjN6e0d5WEcoznRu3gGKihcdxFm5J2Lu57I5lIOII5YYfSplSxGcwUack7vRSde5iq5Lz7J5CMFyqs7Rzz2z5oortGybK5LVUyivirjUAgpBW/h+Pp0r2FOoPjRb+Ka0Rer+vNjJ1fq+LoVehMNCiZtRO0pc3RvY+wpOdBNuvh3G4+rtTan0SG3EYsSLg/9R6IEUVdwhgDzRBJ5YGvQXaAL5U+yv986OUct6B14oMMBx0hBO992XHc+ZlXcPz8Vj7x69V84Q9rGS+UYek58LGHYdn5cMvH4N6vBHsCGQxHHoOABYQNq8VATBdTeoAuKaXWXZjNzs9ahUU8cyNb1BWR4Je/jhfi2L8JdjwIlfCqbYJUOUtbVinKpQnyaaRIqjlEMMTRNaY8pVXCfRt7eWaXrtQoOfcM5bRS7vq2oCrtVu0LniHevHpoZ5UxaNuq/LmM8rdVHzQrs8e7tnqSftGKV7Jt0cBApkixWNuTFjWpO0q2WApuscretqpbMbI7UEihv18pwa7i2zmSV4b7eC9k+tnW7+cYCam8G27VT9/pUl8xAbR+Tuo4vzx8kyOTkBZ7hrKsctsAIGuWXc8W8tC/ybve4dyhfcPBipieAuwKgCpOsWjgmaqxpVQl8mX1YxXvjsLPc/Pm9A+KbbJdtmw//y8wT4RnM2b+lFZEtX1sM0mrwLKue2h0WgvUMu5kOc+S7vsDHmA1TfD9sbl7jDj885aB48Lz5sp+cZiEcNZFnPe8kBardg8xuGuN90y6nqhZmQ6vQqGQFqP5EtlSdQVTX1q0Fkvu+9L/PUz/eBGJ5Kj+J+MNtO7VagTPbVftTXQ3Defie+NFsbj30ehQcyc0OOhB8+fNajmFUe8UISVLu+4OvRaRgyalU/QpEbtPFMZAM1RR2buCxMqfcUPlcq6+6u28dPn86RbJEOLERbO4+RMX8ZnXnMwtqzu58nuPs2rPMMxaBB+8FV52DTz9A/j1O4MNLQ2GIwgpZQlYBVwe2nQ5qppjFE8CS0M5Z6c6P/fUM68e8hdQBG0rUHGsSj8OhYdJIUhaviFktxzlFQkIM7+tESkSWohjNULPNZF2IGwyGJqm9smVKp5nRiIYdBvnAs3FAW3vKLUr5D3QFKRHtvYzlq84K+7+6909qjCBrYcdSYmQFXqcnmopR2spNc4j1zCfYpP//RQw0Nyy1lWNon1S5Wyk5PuGc5QqdrWRmUh68roGVcVShmaieyWLBp729m9w8pJcZaxYcfLZqozwIAK8Z0b3/rn5WPUgpYzwcFnBEDopg4UxQnQ6+WbuM+pXqYxrBOwaojncaxTn1fCMXCk9b0b11mrC3kDPOJC2V8nTd8CoX7pG82zq1TwhpRz0bwn1EYt7hhXuZUoNbvHua/Bgx2tlFWjOa+FuQDLTR8IuhQxc4Yyrh8vW8j654YdhA82faGC8wKbutBe26oolvQUTm9Zcl2pp4KCHCrpeehFhGAWMX69IiHaSrpw1DNUxp5JqbN+yco6tveMMOYVhsCU9Y/nI3Ns9WruM2FBm7XM3VclEnleUMR5vO0V/xlUZW1HFSLxKKpMzuYyBZgggrTJ9v/kE/XIuza/7J9589tLpFskQQ0MyweevOI3ff/xCAK760dN8576tVEjCld+Et/xAVUj66auhb9M0S2swTBvfAT4shPhrIcSLhBDfBZYCPwIQQtwghLhB2/83wBDwSyHEGUKIi1Fl+m+WUtZMHHCVMJVz4eYb+F/sicJQoOKYCFtoVV/uIqAAVI69UOWdRpAAcAyGWkFmbl+qcDiSXmq6NdcdkkuCEHQMRuTngKe7LGlvxlfdQlL0rGF2eocjg03XSB63UqBLd/8guWKF1XtHtDBRiZCWt2ruXrNC8yIGF/0FhWbfOarrW66Btv3xmxHh/kUOC4ZWRL4+nCuxeyjDnGbNdSKB4V3eHLYt2TWQZU2nqjyoG5Q67v1LzzmVQtOiyPnCeAVMNKN5NB9vaLrV6FxsWe1dqVZQZXAhIYRb5c99RN0S/HE+z+D4at8zl7bT2lj9vMb28FMbYzfNH14DQKqqlJ5k12CGDd1j3p1wy/5XsfUu6NtAoeMZclFNiWv080sNRX+PukfMG1nL4pFVXk+xfMmiiN/g3ZdWYEsCFR5rGTcB8SI8aFKqaqngv4+9XC7Na5MM5VXpBlpTMT7krqJZaO61qH50JLFVNmPkD20IVK6U2HSN5gOLSPqULc5nVDrKOwos7b438PeCoZWelP54sup5C0c5uERdH9eo1QkXN5FSUrElDQk/7Nx40AyTRkrJg7/6N5YVtrPi9H/gPZe8ZLpFMtTBBcvnc9dnLuHt5x3D9x7awQd+/hxDmSKc9wH48F2qhO3Pr1AhVAbDEYaU8ibgc8BXgTWoAiBXSildb9hxaKGLUsoM8FqgHVXN8ffAo8BH6pjL+Rl4NXb/KiUn9MUtEbRl9wT+jkMI1R57JFusLugRlkVWy7Wiw1dAGksj2hbpKB2iSvlYPLuZhPBNvWRCr/JYNStz0k5LACekLyGtqjFdb4dbnCKszNQyKvQzaqgo5alYsUhVtFV47eakKrlQufyg0A2B4idAfsT3/gCjTn+z8UKZrOMJah/bjE7CMRQys46n0HJUTMVL/SS0ipdRq/6RiKC3T8oqT0WgAqKUYJVp3XVPzR5SZcv2lMSKI1NbTnk556S30VDyC83o90n1NOtm3qymCEU+XkmXoVDNOCqheEah5T+5hqS+EBLFhu4xNmk5RrZEebCz/eRDhlt5Au9lMEdLeI2tdw5k2NBT7QGSIoEtJQkvMFDWct3oRwYmc40vW0rKznmXbRthl9gzmKZr1Pe+Nxf6At4zCPYTq57Kl2dPoHdbMMTR3Sthl5g7sqGG7NHv24DXW8sxjDRinDkbS6N1VZUM/q3uYSl0L70+dc7YFSv6XkfJ44ae6yRDTevzznyppPA8aLPTO2ovUjgYA80AqA/Mn97xGBft+TFb5lzEm959zXSLZJgEs5sb+NZVZ/Ptq85m9d4R3vz9J1Rp5GNfCh97COYdD7++ClZdP92iGgwvOFLK66SUy6WUTVLK86WUj2nbLpVSXhraf6uU8gopZauUcpmU8lNSyurl0hhsvWJXQHGeUNLAXwJJc8F32j3bMcxwNtqTIpx8Cs9vF5lfFGE1TShcjdArpyq6nx8WvX9V41xPratewa4WJ7g94XnQjvJGixJ1fPbJ2su+qqMrdnaiMf60RdAQ8GtrqF90G+GpHQOeEqvnoYUHtBMNVaGH1Xv5ZnihOJnelsFwTCsRLOqlG2j5igW5QajkWRDqGRUe0VVcXbtS98LontawoT1nbGvsckKhUp8HIVooqd8MQDVOdr1WA5kYz9kEdI3kYd9z0L+5qtdfXC8zXSQ9ny9pFZk3vJZkJUv0+0e9cfS3aNjD2RBh2YpQDlqloY2x9hc7IcH+60u772dx72NOuKkrU3UooFXjWYwMCQQ/xNFtN6GHSVZiPOwa+pQV22Z91xi7BjJUbDvokaqRb5uw6r/HpdCzFvREq9BS/b7qDciTlVCeZY0FMpf2saCXddgJ2UwlhFdRMyHLwZ6MMRgDzQDAf9+/jROe+xdSCcGpH/4RIq4bn2FG847zj+GPn7gIIQTv/NHT/H7lPmhfBh+5B056Ddz+Wbj/n2p++BkMhgMj2oMmqg2VcNNjZ5V2fNaJUQNRtKTfrD6E7uuJD0Nzt1cr1HEV2Nqy+1TuS4TBJ4S7+q/+Tgh9pTloMLg0lEaDeSuRs/rXpMqD5uZENbZXHaMrqXkt9BGRoLE4RMIqaWXHodQwp2bu0azBNcEXGloD+VP+OWjnmnAKsTjznLF0jve3nWisOZ97Fu4F2tkfXzgieETQ86RCHINGQ1vWbzy8uXscSlmQ1c+Bjm1LzUCb6DujOqRSFKIb8WZiwtIEEnJDVUq1zrKuu1nS8yANpbHAnKmq/LSQdFJV9Vy7L1qmQsVS1VRjaCwOxxo0Euk9lyBpyffSmutk7mhMaoFIYOPfn7SXj+nj9o5LBt53QU+bFEkqqbbIKcLXQ4bynwQTGGixr6tjErHLMTHHRZTs7xktULZshnMl9gzlAkZkUzjMWpMpNnw1gqHsBPvGhCQDLOp/OrCthvPeI+zhd4dPJYKVdTd0j03oTTdauIHvPrCdLY/8lsuTq0ld9hUS84+fbpEMB8BLlrVz+6dfwcuWz+fvb17HV/60nlKyDd77O7jgo/Dkd+EPH4Jy7aaSBoNh/1BNiYMGhhSiKi8oIZSiv3rvCNv7x9kzmAGRIDtLRVwK7CrFKhbheOucfLHYPAdvtb3KhRa5+6xMh+eVC+MqmK7C7XrxwuPpp63Ck8Kr2JFiAnhl3705wwqQpsAGCPNpmAAAIABJREFULq/w88eErLBo4BmW9NyvSrKn2ig2zSdVyZIc3kk0oqqZNwl/zKCxrZ2rSHkvpRJC6x0qsBJNE0aypSpZ30sxQYij7cwlE8E8L8uWDGZKsdUFJRIGtkZu0w2C/vGCV5xkosjMcA5V0i6SGNhch8/BZ1amg7H+vazrijaiFJKEXeSo/ic8b+i81sYa+7tHKe9auYahWSoVIw1RYVdYNPB0TYMmoS1qux6e5kJ/ZG6ZxHubAtA3Xoi8162NKY6Z3xI4UC82IkUCKURVhc1I+exqo7h2S4TaHvWonmT1oO9d0MINC2WLlrxfWDdZrF6ccOec6H2hExcSXW6YrbyYVUsm/l9hQ7AeA801XHOtxwB4JfmTWl6yS/foBI29J57OcLgipeS/7tnCzx94nv9qvRG5+CUkLvzEdItlmALmtzVy/dUv5eOvOpFfP7uX9/zkafqyFXjjt+GKf4fNt8P1b4JM/IqhwWCYPEMLLsBKNGnWgmaohXSZfNliJKtCYMbyZfp3r3fyQhL+saFjhKYguQq6el3tr1bO4zQJpzm0rFaohZTsG47zQvghmwBWstmTAWAoW6KSmoVsXaCdr/o5OveMwClIkQyUS4/zAHjFHkKhWWEDLQ7dsNUr7zWWRrCSTUjRQMrKkexdS8Iq0CjLXqlxF12BlUiw/SqBtoSh+ec556p7NRIc3f0AAhshhObFEtjJxip/1eymoHGVtAqeV6tWMYH20U2q0a4jnX4/ixWrShmMIkq1Tgg4caGqFNqvVe0M533FjxBkMgYaqCbOLsPzz6nrmIbkxLPovQnjPBfrOkfY0BXhoXaMm1oGTVKoUFpJsMJpZOEMkXAMNF9u917rRW/Cxo9Asj1QSCMJCDoGg4sYUUQ9S7Xss1oLPBDtEasLPUTT0sIjk4KkFroY9pDbycb6F6s0krHvAz9gMeANr3E+DXq/hRjcz6ewrMp+F9iJJu+1wQnCcY2BdoRi25L/c+sGrntkJ79Y8ifmWCOIt3wPkqYZ9eFCKpngy294ET9833ls6R3nTd9/gtX7RuGia+HdN0LfRvjZa2JXUg0Gw+SRIoGdbPKTz/Uk+NC+li3pGPKVKyFtsH2vmSp+EK+kWyl/dV0IP2m9qTAQo2BFe33cv3WFPLgpGOJYdhr06jkZdqIBEkntfNXPcIVBKRJevhAIShGhioMLX+ZXxAydR63eXTIwj18oJRnKWZEkvWssnTmW9jzg9bUCdT3DevxQJu8p+raUVBrmODJqBThE0lt5TwjtCgmBFKk6FdqJPWizMh2+rFIyb2RdaI/aRkuuWGG3W0pf31eIyPL7UblzrvHcWByq6lE2sQQTU6y76uXEM+lGTK2G71EetuMcL1YtT1UyIaKN4igPmkioIjmB6EU1b1lbsLBsO2SkyWA4reNBCzO/TRnui3sfJeW06RARRTVqP4nRW70QRzf0tU77TEoYnn9u4NPMPbfBhS9Hti4MzDme99+zpYZ2xtpfxK72v6hvMg19QSc959SIPWToHsWf0KJZ8Z7axbObOXnRLO+ehg20lF1CIrAT0VV4ozAG2hFI2bL5/O/X8L/P7OU/z+7lgpG7EBd/VjU4Nhx2vPGsJfzpkxfT0pDkPT9+hptXdcKL3gxX3+lXeNz77HSLaTAc8nh9jRCewqWXZ47LvdEpWXagd1GY0blneL9n244j16JaoaQSCVryenPkCEXD6bfUMZSlNddNqqS8BS87YT4gaWmMWyEOetA85SOUHyMCuVDuTxGscidtrVBH0POTb17M0PzzKDYvYmTe2c6r4Ry0sELq5PElGrAWnKa9nmBowQXenIGzSST90FMJLfm+iNyRYOEFgJ19Y9p2kF7IVbTCr3R231CUIlmlr0eZFu41CYaC1kKGKm+6eWnx6L3BzjzGN5ITQmDNPwkr2RLYP8o4acn3smBwBYsGniFVyVR7OOKKidZJ2Pg4YUEbc1uqleQ6nIUB6vE46bQ3K6W6UsMaSSUTngctIFvE+9C9N4nAfs4zpF1Dy4ZypUYoskgQdYHdsNpUJeM9F8KOMvZr5KA5z6DrTfVkcry27mdd7TDJIIXmhQGDU6JCAYtNC0gmE4H3kX7d0u2nIxMNVBpmMzLvzLrnq15o0DN13c8qGfiECVe6dGlKJZnXFm+gLZjdyNzWRm2G4NwqZ5LabssQxkA7wkgXynz0Vyv585puvvrapby7+1uw6HS49B+mWzTDQeS0o2dz66cu5oLl8/jCH9by9Ts2UTn6XPjofdA6H254K2y9e7rFNBgOaZTOolbSU5Usc0c2eJ4Or/DHBKiGwE455vFdVdtLTfMpzz5WqRciycj8s5jdlKIxmfCNHS0HLexdcPdpLI2wuP9xABbNamJJW4JcqUbxBpQBpVb/Hc9USou4kBKEr2T5Da4T9I8XvRA5Ia2AZ8gNKxxacAHDCy+g0LpEHedWPAsplnH1q6QIJuFLITRDN9wAPEnKqRgnkbRldlfll0Q5S3QFMlip0x9fD6d0Q9g8Q0NUZ7xAtRIczl+MorXBN6YjlUoh6srNCpMQytgIr/TH5RrpVUZtEaocqf0/Efr5uEiRoGfJa+lZchmgqhW3RiwiTNZACzTsrgOBJBGRQ6qjDPyo7VEPknNltIfOfV+GDesooyBoCEdVe4yYMqoBdU1bwfmcSGkGoxaeV2+0oZuLJZF+fqY3v1TVVoUgnQ/JJyVWspneoy+l2LxQk6r6/ofDpMuOZ9vN9fOO1YV2StAKKbHteEOznFLvzfaWhhrhkv41dz12rc3B++b2xowrxhSFMdCOIPYN53jn/zzFUzsG+c93nMlfZ38OmV5423WQapp4AMMhzby2Rn71kZfx4YuW87MnOrj6+hWMNR8DH7kPjjodfvdXsPrG6RbTYDiEEV5oXcrKBXqYpee+KPKIYtNCik0LA6/5xokK87GSLZ6nDMCSejNqQUtjytH5XKsoWrEXyEhFTQhBg13QcprCqMqQwwsvoHvZGzztLKGFxAvcqgfVCkjZsr38NiHtgOHhev0KLYsDx7genGSoGl1CiIAX0feyBEPMpOZdCPf6CuTBSUjahSoPmhvSt1BTkPVwU6XPqWMai773Si8V7g45R/P6VCnFAmY1V4c9tUQYLC6phOD0JXNityulWHDiwjZKjfNi94tjdnMDjXOXBV6rFRboYicbWTRLU+KFqNt4WjArSgdR4cK2k/MYusX+XpO10CaLlNhS1vSAJ4QgKWyOmT878Hp0kRAnhFn3t7he5dC5zGpKOQ3gfbz3qbQjQxyjiAqVrt0wXO0f8EIJ4ZXST9RpeI+1v0h5Fm21gKO3vEDzQufKduBzS0gLSQIrZHxF5aH5LTeCsqt022BIqI7XEB7pLIxVI512FcLzhqsohsysEyL3d2dIJYLvX/8yGgPNEOL5vSP85XVP0jtW4IaPvIx3t2+B528EE9p4RNGQTPAvbzmD/3zHmTyza4i3/vAJduSa4UN3wImvgtuuhce+OSk3vMFg0HHClzTFaWIlOUJr18i1LmVkwbne3xVLNxCUmtfaqBcM8Y2goN0hI70yApUjYcUZaJIYzTgZ3EkkCBdHcU/F8nLKLE+BqpU7VEm1AgSbTKM8FXohhcBZSH08Pz+nuj+TJN96tH9q0q6uDun8nN3SwPIF1YVMbPy8vMaYEu9ePoqmau3vR6secigQsUbJ8PxzGJl/tnPL6lXefUX8uPmtgGDO8cECHWVbTvgcW4lmFp11edXYcehGsdXQGiFY8OhUItrgO1D7LCrnLsjEN61i25x/7FwWzAmeR608Qt0brOdl+rNGz2u7RkPMQkw9z1giISg3z/f+zrYdz7HzWr38Ndd4ibs29RvFkv7FryC94CwA+o6+lP6jLvby8LzzFYmAd0m4nydhRNDw6TrmjZQa5wZ38WYmcOsm8jxG4RrDuvfMFg1IkeSkhbNodMJJveAF53qFP08SzsKda7AXmhZNWPTEGGhHAHes6+Y9P3mG1sYUt3zyYi46qgx//hs46gx4lQltPBJ590uP47cf+wsyxQpv++FTPNSRhffeBGe+Cx76Otz1RYiMWTcYDBMhheCcY32lwVUg3JyowL6hHlaAGw/j/xlSxCq25R/jGglaKJJwcs20zQDMHt/peeXC0yVFjEKEq6xpAznytDZrXg8pnSw0t4iAf7T6W8/OqK38gfJyqXNRiqvbeDopRKRiYyUbg/ZZ6BoGzse2GJ37ElWcwK0WGVI4XYMyEeMFUhGbakNKRhdXcc9ZrxooHW+MJk1dquLIvLOqXjt7SQsvXup70i44fj7HzlOGXGODUuKliPbEKYPPD0J8ybJ2zjpmLrObG0AIZrVUFwwbn32S93shooCHwCYxe7G3LRziqDcPBzh6ju8ZkhOooyPzznKKrkSF9O2fhZaec1p9x8cYQvP18EPv7Rgcq7lQXSnZff4b9NL8znNeT6VC12gIVx0NiVIbpyXH6NyXMDr3DC646DIWa/fDtTh0QyNwjyIuWaF5sRcS6B0jElQaZpOddTygChuVnc9D3QsthQh6BANRAsHxJn5N6qegEbVfcCd9oQt8YzilVwoVYCWbSCS0z11nGHfRIZVMcPwC31jXP/8aEoLReWdgJSMWJWpIaziMkFLyw4d3cO1vnufMZe38+VMXc/LCFrjlY6oH1lW/hIbmiQcyHJZcsHw+t177Co5f0MpHf7WS657Yi/zLH8GF18KKn8LNV0Ol/oaQBoMBlMKRCHwhuwpEoWUxba3RZeXDBEOXgkrEWK5CuqCFW1UpSzIyB03vM+QdKgRCCJJC1lAOg82vXQWzuamJFx2tDIThBecrQVzFzpdEbXfLnEs/zPLoUOjWKUf54WGuYdHoJNfnW5THq6UxGbg27op0uaEdKcMXIsZAwwaRoNww21PiqjxoMmxo+iS9XDK1MRnjJXGfgRMWzmKOY/BIqisiCvxcneDrwlOao6q/tSQlrQ2p0DGK+bOV8nf+ycs4/qQzsBONgebddqLBv6dCFZlxvQFYZZojSorrz0e6PaYiHniGvmgNetwqqWDhEVeZLTYtiPT6tLc08KazljojqzEXzmpkYVsjTY58rY0pFoSq68X1vgpT/v/svXmYHFW5+P95q/fp7tn3mUwmeyY7SUhICBD2VUBE3HdRQdF71Ys/vHpFr1f0epWroijIVxQUNxSXC4KCyL4E2fclEMi+J5PM1tP1++NUdVdvs2Vmuid5P8/TT3dXnap6z6ntvOddTiBGb7AqrwK+qfG4jGrla48aj4LWVOlOPZF5D4W7Nxc8vitnMiM2a3DZe0I1JK0gnfHCca0N8dy+XVnQn544HeNum6icwoyORUSd6R7SDsPpAYqh0husIBGIOb+r2NxwTMpFMCfGy4b+jOywmWqyZSfyDhjlf0ZluS7aSTPPGZlPTp8vz2BFllzZg0bu8bKvKXeqkal1MZorIpSF/FA9JaV025afulj6HKS3t4mGAiajq1rQDk16E0k++5sn+Oatz3P2omZ+fv5yM9pz97fg1bvhtG9C3azBd6Qc1LRURvjtx1Zy+vwm/vsvz/PR6x9lzzGXwklfhWf+ANe/BbpzJ4xUFCUXwShWbur46mjQ2JQ8VozGyiwFTSQjTsW1UnhHq7MtaFv2dDtlXOtU5i6neZJODNZZje99BZ78LcGurQzV7SdlURAfIb9FV7iBRCBGWTiQinVJHTergyce5THg8ygFQDTk6UBlJfhw62rKe7suaUtiTr47Zx8djeWZ84057Z30hVIdyBwLWmpE3MpNtOIO8kvWgizcxfGQnxVTa5xDZ2aNcw19O6sW0BlrTy3v7U9iYxNyRugLWcJyjul2rB3303BZjGD7MjY2n8guTwY8Wyw8+lkmezY4GT2zO6vpNnSvT+/5SyW6cCserqQ/nM4QOashMwuf2/nfVruMfslVQLv7+vFZwqrptSxoM+54PsuivTaWur6a5x+bc+4GSuaQiZAUf47Va1vtsqz2tpndlBlblk0kpSgPfGyjOLnnyNm751hDsaDZ4mNj84l0lTUXLJOdTKWpIszstmYii85jf+tRTgINm0jQz2SPC6/XXpaNlTUQkR2HJXY/jRWRVD1cZQ3yT9OQWScrx1KZLxNpxiCBkzY/Nw7PZkv9KroijRluol4FLRTwI8lExtQakPksjQR8LJhk7tt42GtRFpKWebYHfRbNlZHUcvecbt2bad10RUz40u1TOObXkWXAtcqEZOe+Xt5zzYPc+M83+NcTZnL52xaZ0abX7oM7LzNubIveVWwxlRIhEvTxvXccxhdO7+D257bwpu/dwzPt74M3XwXr7oefnA57c0feFUXJxH0Jp0ZXa2PUx0OEerany+QbxfXgul0hFq2Ou1q2guZ1Z4RcF62qlhmpzs5gEztX7H7WKTdI5zDDRdHB8uP3pdMFRIOBlPJTEck/309870tUy17KQ37KI34qPK50+RNFZB5fJC3nlNp0x9LMEOVYJFIdH/M/4LMyEnF4VbmupuXsjzTn6FhJjwVtMLucJZI3PitlfZDMbu92zwS14pYTod8XYWptjFjIn3KxdFOmezvx+2JtGcdpqYwQS1lAHLndFP0Br9VKsn67bZpVIxHCAR+N5ZnnIzMLnpWzrd8yCltqcEEkFTMUC/lpa23LSIiTtG1j6RArdc946UmYa7gmFqKxMjvTpSNTvDlH/qFa0Gyx6AnXZbRKvxWiJ1yX2em3k/gLpQ/N3euAaysigdS5TE3L4QwSNMTDKZe6gUnLNtOxYCetIJGYew3aOZYvSwQrEATLoqsvyY59vSSTyVwL8QDKbbZ79P6ydCKZpBVkf9mk1D2YnbGxcIIVrwUt8zlXFc19HniVmr3lM7L24fxzMsruLp+RaSCLVLO9ZgnbapdTFvRT68udbsHbbv1Jm6pYhKWTqzMGIsz8c768ungq62Yyz7xzImyvPZzO+iXYVoB+38DJ+VRBO8hYu20f51x5H4+u28V33r6IT50wwzy89myA334QqtrhjG8PeBMqhx4iwoePmsovP3IE3X39vPkH9/KbvpXwzl/BjlfgmhNh20vFFlNRShrTmc6MkYoEfWmlC7ByXNXSz+Jttcs8z2Yh6sRDDNZpy3mcty5NxXn4B3jUb69ZktrWRI8N0CXIN5lrqi6e9P7OkoATs1GeZ96qSMDHzMZy/JaVUtDmt1QMmLkwU5kwvxe0VnqsjwJOZka34+h14bNE2Fq3AiDDUpWI1NIZn2JcvvKMaBvlKb8s3igrW3y5cWLBaKqc2849dfNZv6srbw1tsYiF/BkKuCVQGQlmKGjZme2aKiLMdjrqri7vSyloUY/FL9PttuBcac7121pVxtTaWMpdLsOCJum6g3GfWza5ygwIpC4qK7WvXQ0rIFxOvz8dd+OzJLVPe7BM0lkWxJTDWJ6+TF08RKCAkpZ9jXXGp7Cr6UjPjl0Fw1NuOJld+vKfW+/u3evMFT3pHCvglyEpaN46t1VF8VlCvy9Eb/nkjOPkHtwcJ4Fp8x19gVzrMPniAYXN9UfllPN7Bps2Np9IIhDFPTOD1aMjZZF021ty2rk9Z/oJ8iryLun4N7OfRCDO+urlqfVWqIzuSCM94Vp8fXuZ2VDO0snVKXdZMNd8VVmQxvIw0+tjWYmQDL3BSmzx5b17Uopc1qCa285JX4ieqLF8qgXtEOKBV7bz5h/cy+6uPn5x/nLOWuSMbvR0wi/eBj174bzrIDSwqV45dDm8vZo/X3QUi9uq+LffPsHnHqun+103Qe8++H8nwfpHii2iopQ0AZ9F1E2eIRa1C09l5QKjoFWWBbF8uZaldEKMfs8ySU0cvbsi0x09O57DtSB0NJYzc8WZIEJnfAp74jPw+Qq/5vsC8bSqIWTEfNTHMzvMYc+E26nOa6QKLF86eYQT6A+kpuz1DeKyVVkWZGZDnCm10YzR/HktFVklPQpBnt6nDfT3GaUk1YlzpwPAxAb1hqpZ33o6PeF0ggvbmc+suizIlDwdQsvKk0JCMn+ImE52VUtmXJZ4OnfuyHx/VhwWCDL/3PT+svRBS4T2mrIhu8G5DpRWv2PtCJd7lJnsLHbOmkCWTJ5y1dFgSmHM3N78TsXWeRLTpH0nLV7yT6cnVM0uSScz6bdCTK+LEWvuYHvNYgDaauIZcVM5mTqzOsoisKMqM9MkwOTqMurjYRZOqsqwerjMavTGOZr1yYBReCsjAZZPqc1pg3xJQnZXzMlZNhBzmstZ0FJJJOhLdczd29h26mbcofNbnr2kpogAAsEAFmYuMJ8no6D3FklKwPx33E0TgRjba5Y6iVcy9+21ULv0xVpIBMtZ3Ja2EgsQ8OeR1W3TQRQ01yKZDhvNzOIIaTfdfPvPxHWtdcp7no8b9qbPndeymro/SF8TnbF2grNPYlpdjNaqMidhSGYD7apdQtIXLuhy7Jt2rBn4cp7lkYDPc9zMfe0pn85AqIJ2kPDbR97gPdc8SE00yE0XHsnSdid9arIfbvwwbH4K3notNM4rqpxK6VMXD3Hdh5bx8WOn8etHXue0G/fzwuk3mtHga98EL/2t2CIqSsly4pxGVk535uUJlEFZNRWRACd0NHDktJocF8eykJ9dlfPoDVbRGzTP7ZXTapnbUoXfstgXbcuxHuQoaM53NBqlvKYxtTwRiOLL1WVIONnDklaIhJv+HjOHW9+M05mx8Cgqsyxf3gx8GZ2vuW+mtcV1uTPj79Xb1lC+5WEAQnmsYtn6VXk4kEpWsmhSJcd3NDCtLpYxuu925HJTx6fb4rUd+5yymV0byxIijtJckZWd0KgV5kh18RD1WckVfJIrry9lZfHIZ/lznNt8/d2pCqeUJJucCaTFY7XxqE1GdieLZEaHMLuT6hl0dZOb9DYfAbUzCro4GhctR8EMZimmOQMA5ttrvXDrXhsP0hPy9DfwtL+TwW9b3YoMmbsjjVREAkhVe2qOs4Dfx6TqtHVte21WxtM8SVJ6wnU5c3nVxfMlZjB0xqfhb04rdalsiFauuybAnKZyxzKZa0HbF52UY30aCL9lEfRb+C2LRQsWUl0WpDISpKkijO2Z4DtHsQnFc47j8ygXEoqzs34ZO6sWIN55CT112VFzGCBQ48nCGWnAtnLj78wIQeY9u6yun9PmN+W4Tfp8wp7ymVnKqp2/HllkeWl7LGjpY8ggrqqnzsuUKRQMEgn46HImuzdypO+1fAo7gK8sPd1Azs2eda8lIvXOfn25becPIbE6uiONKXfNuYuPYtG0Se7OgPTVZKsF7eAmmbT5n1uf57O/eZxlU6r53YVH0uZJ7cltX4QXboFT/xtmnFh4R4riwe+z+LeTZ/PzDy1nX0+C03+xkevmXI1dPcVYY5/4dbFFVJTSRCRvZzIacuK1stbNrI8zubmBrfUrSfrMC7suHiIWdkbZ84wY5wTcu4kY8pT15Ymd2RdrZ33r6diWn55QTUpsGwvbF6IiHstx60t4XNM6o44rVdwog/NbK4zHhpg4kkj3ZgJO6vmg3+fMrTU0JtdEU/FUvSHjpjm1NkbegA9IxefZCMn+zLmk3BT9AlTE46yeWc/iyZmxYknX3ODsPltWq31l6nck4KOpIuyZONhs5Lck74h6f9Iz8a6rhCEFJ31Oii9HqTDhaZlaYo4LWsRTJzcBSrQemhZmHDtTQfN2hC1oX+XZR/6slJkuZ651UkhaIXNYJ+4m4PMZV0KxUnPIefWoXZVzkanHYJV5568aRNnJum/21i1N3S+F8FnC7oqO1L57gpVQmY7f8zlZrF3Lkwhg91MbCzGlNkrZkreb+zBLCezzx7DFh53nPh8K5ZEwU+tiBP0WdfFwysUxRxEHaFmKZWUm5BC7n7p4iGVTjGJhx5uwrQBBx6Jlk7bYdofq6AnXsW/m2Xm9pwJZIzgCqSRHk517wecPpGIhIZ1gxu/zs7d8Bp1xj2zONTCYgpZrVcqNQZPe3BgxL0G/cZF23ZzLwiHmHv8edlWmDRGuHH2BeMF4XKvcPMfMhPMDK2iSignNc+5rPBaxMsdKH61FwpneABnTGQyAKmgTmO6+fi765aNc8feXePvhk7j2A8syRwfv/z488H1YfgEsO794gioTlpXTa/nLp47muNn1fPGO7Zzv+wo9zcvMVA33XVFs8RSlBJECbjiGlKubZSw6Ab+Vx52P1D6WttewJEupcBNIuH2JnubDnf+5SkIoMPBrfnvNUghXGFcnV+5kItVNScdnpDsuiWA561tPh1CW5UWsdHiaJ0FGOMuK5rMEorUMxpY6oxyZ7I75E3F449/IyiLoWnxEBHxBKsoCOWqAdy6mfIhnAmURoaWyzNPRE5oqwqaTbQUz+vF749PYX5FOYuBuksSisye/AmRb/lTCEBdLciel9vsLW9OSqQnK89TJWdZUEXaUPE8nOd4Ik5aZvyHHHTFal29zI6vnT9IKmrPgdM5XTKtlTlM5BGOpzmiGiiMCsfpMZTRL3uVTajh6huf4We5uPZGG3P16sfy0VZURqmrx9Iuy2taJe/NZnhTzyQRHTq9lQatHecyasqIzPhVE6Jt9JvsjTibFynT8l5e+QJykFSQ54+SCdXUVPROflqXY+PzUr3g3e6vmsr3auIOKnWDltFqanIyJi1ormdtcnjEvoXtVbK9dklcuF38eq1J3uJ6Q35e2RnpcKiE9QJBv8EecsoPGzWb9spEcRVj68k8A72X51Goam1tJ+GPsr+oAfzCzfUXYUr8qFX+aV5Zycw5DJPJY0LLuPSttHU4mbXCtz7Uzwbmejptdz4rFC6DjTCirBsuPzzJ1rI+Hc6z4hVAFbYKydW8Pb7/qAW5+ciOXnDqby86ZnzHCwUNXw62fNxfIyf9VPEGVCU9VNMgP372Ey86Zz72v97HqjY/zRtNJcNu/GwttMv9osKIcujgv9TwxFFbYjGK7KbILZ5wzy2PhEHVZ8WDuxMduEhEiMjBYAAAgAElEQVQrpRV50kj7TQe80P5ddx/b8kPYmTjWa1VxfrubZydjyOjAemR240gy+kjhCjpjU0iKn8bysOlY1s/NK1c+RIz75da65dBxJo3lYWpzMj5KqiNtY9oh6QunUnEXUpptO3+iiexapQrjScUtQkM8bKwOgfKMbdz6uuXc9uz1lWFjZ8yLlJJF0qnaXQWe5sXQlBlrlTc2x8E1zvnz+bYCO6sWmkxz4on4cdumsg2mHANtR5j/7UfBnLMzthfESbThXh9CvxU0roaO5U1qpyMti6GyLZV2PGceLLJcCh0Z5jSX09FYTmNFOJ0RzysjwIyTclyFZ9TH6Dj+vekFlo+ykJ9V02upj3snlPbI4Rw/bUGTlJtmZpnMa3p/dJLTFqTjRgucky31R7Gx6QTEO5ghmeqJe50Igm352Vp3RHowwgpgWcKU2mjKYphtQa2KBpleHwdvfKtbZJDpGfq81tw5Z7Gl7VST3TLhaYfJR2ZuJCZz6/T6fJk13UGSoVkXU/eeWI4FLX1+pDptmVsxrSYtTk1ZyhU55PdRXxljc+MxJIKZ96BLX7AC28odnElh+ZlaG2Nuc576ZGfD9CilnVNPgRknwbTjoDE9fUQ8HDADW37nuvMHUwMmiXyZMwuJNbRiSinxwua9nP39e3lu0x6ufNcSPnrMtMwH3QNXws2fhZmnwluuKfjgUJShIiK8Y1kbf/7kKtoaqjl67Xu5I34m3PdduOkC6O8bfCeKciggYlwOo3Vpi4SHYPN8ahefxeFzZjC3uXzw9N2Wr2ASudTkucGYOWbzYal1q2fVs3xqDVaebklDRTgVe2aO4crgdtQnYztuOYLp/Ga7WlZH87iXiUWOTcMK0D/tBHZXzsGyEzRWhE1nxfKBpwM2OE5sjD/I8qk1HDk90wJnexQ0b5Vtj5IEaYugGwf24pa9zr4zj5ZONJK7zvu+tZw8/Mms7HK2SN5kLglfhP2R5tR52d5+Rk5NvR1NKW+A2sxkAr6MRDN2WunwBegsMy58XgXNG6eVtIKUBfwk/NF059N7bmN14MYyWRb4/BnX3+K2SuY0laeuB79PiJZFmFxTlra4heIm3kkkpdwOngjRlCsL+FOTJmeu9sgYTrePu9+KSJBoJJx24/OUT00eLFaqbrsq56bPo5hYzwJOtKnrqrIs1/LRE3auw1g6qcnmhmM8m0tOJ98rm5C+dtxSvaEattUuNdbtoBMvatv0hmrYXdHB7soCgxvufm0bu2UZG5oHD2vZ2+15d/sCbNzbR8YF37jAWIGyDyVCTSzMWYtaOHmuJ+417Mz3N4Bi2NHkVaSc68OdtsEdZBEf0rw4LZqnDeti4QxX5OHEAubF8lMdDRL2peVJkXXheuWIRKLmHimrzj3HGRuF8PmMC2dff3LISUFVQZtg/OOFrbzlB/fR15/k1x9dwSnz0jcGtg13fBX+8v9Bx5vgvJ+mNXhFGQWm1cX49UdX8PnT53LhrndwBefBE7/EvuHt0L2n2OIpSvGxbfPcnXpMOjbMi+WjvbmBaNBnJrct9GJ3O+Gu25sH1/bhvuctn9/EGHvcBsMBHxWRYE5/Y0FLJXOaKlKTQh8zsy41yp5SwiyLRN1c56c4k7QOobsgQmtVxKSFdzPUBUIZsR+pDo6IsQ4NAafrlnfd3OZyk21NJBXz5bUwpK1j5jvotzh9fhOzG73xOLn79rpFZa+1siwg4Lj5eZIc2OKjqbIso5QAiaTNzprD0m3itPnRM+pYOtNYZrrik9POh3k6uj6vi6O3t9e0iL48E0h7dfH5HbNh8kpmzV+Wln4wC6JbDEklczmho5G5zeVYIiyfWkfFgjOgbWXOtikL7IBHGFyGnFigQuWmroapx+KtW9jJhirJBFg+1reezr5Ye8Y+9kUnFUhNLyYTNtBeE6VjedpVMRTwmXjOllMykrFUV9dSGQkwp9GjaHuPJlY6Fk6gK2L6cUmvNdUK0h1JK30zG+I0VUTojE8tHHvncSu0AuFBk1CURwLMa858RiWHYFHOxuvC3F01m+01S5nU1l6w/MwGc+/FQn4nU2JaobMcN9k+fywjSYjfslgyuSoVd5ePwa6xaMjvxLNCV4Vn0MONJUwmUm6K6Z1mWhi9c7NV5RukyocvQNjvI0g/sxvL81qT86EK2gTi+gde44PXPkxLVYSbPn5kpotJX5eZ5+yub8Jh74Fzr8290BRlFPBZZs60Wz51DHc1fpDP9Z1P8qU76Lv6BNixttjiKUpxyTNB6YgIpecJCvqt/DFFDgOty17j7mtBayXzWyqoLAumOr/euJFkfzK1vSWSSqfukp1cwD1aY3kkw/XJtoKZCo3XauPEhg2KeNNxZ9IQCzKnqZyQ30fCdcvKSSefuczvs7KsbLlj8ElfiN5QNSBkZ2vL2Luzbb9jmYnPXEVfoBzEl554282WKOn4wV5nEuZNe0ymx6pokLqqCph/Ll2xyYBNyO8j6ChjR82oY2Z9nPKQn1lNeRR/h4WtFdTFQ5SH0+fLtaBVlgVproxAeTMtVWU0lEfytFcutbEQdbEQMxvT5zUaDpgBBnf7cHmmi52D68rpylAok95gMhRS4Ozsbrk/BNGajPLpKQ4KJauxnUyKeY7R3wcJc46s9iOJ1qVjzWIhP3XxEEun1GXIv2JaDdPr45TlswSCGRCZtAzmvQXmnUu/P8KOqkV0NizPXx6jBA2knKT2i1FUhqJjHTurnvqshBXeQQazz9wdJXy5181hk6o4dnY9iNAdaSAW8pvBnyxCnvSNsxvLOXGOUU7TFrRE6riZlmozR5kbd+cl7kxC3+ysO2VeY0Y21lmNcVZMrWFGfYzqmHne7K/2ZJ50FTTbNhbWjjdB3WyzrL83Xc4XYG5zfjfKAfEFsEQ4vK2c5srI4IMVDiNLQaOMK/1Jm6/d/CzX3LOW42bX8913HJbKcgXA9pfhN++DTU/BiV+BlZ8c2t2pKAfAlNoov/zIEVz3QBMfvqWB/912OaErVxN458/xTVk1+A4U5WDDF8rMqDcgg7ymU50Go3TUxUNsdjrzqT04fanCXpJS0J2mNhZKx3F53IrS+86MuzlmViN/eHJzan1e18ysTraNyVrpG+h9NPv0wuscLBEm18TYtj9fvKuRs9+GRLCScPfmjIyT6RiXbCukZPwbjIQ/Cjjtn6fqtpMoY9bMDv6w3+3EZSl2IiT6Xetn4fOfSCbxA82V4ZTc1dEgRAJGUfYkg2DK0RkDY5VlQVZOy3T/dC0cLZWZndv2Sj/t5dWDKkem/aPgL+C2NkA2w2zl9viOhgIWhGH2WYZTvHYG+7eupy+YqdiWhXzs603gsyySln8Iu8wtkWrr7t6cdRlbZlxuVmqhu7wr2kJ3JA579g4qRcFjeOLyTAKP/MloBqPgPHszT2Z754v0BiuRtkCGh5abPdzrTltZljv4cso8JwV+00LY+HiqYWyxCPl9dPW7Mme2deFYXWMZO2NBc6pMyO/LiPOaXhdLJUPJuxf3Wea6cvpD6YGjrPCNQpkgB8RroSN/PGY+VEErcTp7Enzqhke5/bktvH9lO188Y076QrVtePR649LoC8A7fw0zTyquwMohhWUJ71vZzrGzPs6Xfz2Vj2/8d9p+ehabjvoaLcd/tNjiKcr4EiwbweBYgfKusuQkLchnJetNJsEHIV/heI+8nYFs10vXwuNJr+52RFLuS1mdtrwWtCyvDduxyOVvEmfhEGKkBVjYWpXXQuMql36fxc6yKXRFmkg4Ew+vnllP37a9sHs92e2cExaU5zw0lofBTmYkcvBIPnQk3Tncsrd74LKYvEv7om34ZFN+5cfTwSdWn1bQClx74YCP0+c35WbsS2ZOSzBiBlTQMv8HsybAWjalmp6+JMjg7eLFuMb1DBDD6eknNS1k5+bcrKGL26rYvq+Xrt7+wlkHo3Wwb6uzy4HaKc86XzC/jpQVg+YSyDo/2dlbB8ONt/Sm2R8uh7dX8+Szmz1LPPsJxdNulxXNI9p/itoZ5oOJB60LxZgUivLcJqOgtlRFM4oPVp9sBc4usK7gbmacaOatdKlqh85NUDcLtr804LEHJWuwLTBY3LG72YEdVRlL1u/q4twr7+POF7byn2fN5dIz56YvtJ2vwnVnwx8/YUYiPnaPKmdK0WirKeNbHzuH5874PWtkLi13X8z9P/gIe/d3FVs0RSlNBhtFdRMhBNxU8Zmr5zaXpzKwDZRK3z1KeThAx/SpMPMUkwgi41gVTgdIUvuqLgswpTZKa5XTaRHJyKSWO8EtOanz+51Orz/fqPMw5pDKngcsAyc5QyJsAvVd5QygoixAbdx1x8q2oBVmSm2UaXUxlk+tSY2g254OfLBuOgm/4+43aRmJJhNLl3NKs5JwDLXPnEgm2VMxi76ON+dXYEcw/1a+dOopDtThZgB5ButYN1VEaK+NDlgmH/NbKljaXp0/WQ3kNPbJcxs5aU5jxrKAz3KsinZaafJlKWpTPQk/Bmqo7HrOOs3ca/m29CponhXT6tLt4LMkfe8NFc+1MhJDDxhLfUELmoe89z9mzkKfJTlzfbXXRHMS+7gcPbOOjmZXGbUJ+CxjsfUcK3uqjsHITNaZK2vOsnBF5rn3B411OpDrUjlssixoQ41dUwtaifLoup2c/7NH6Onr5yfvP5yjXV/eRC88fLVJBiI+OP3bsOQDA/m4KMq4ICKcvqyD3XNv5f6fXMSKLb/i0W8+wfaTf8Dxyw8r+EBXlEMa5744dnY9f39uS3p5ZRv4w8ZCQm7XMBLwM60qxj93Z8Z1ZO/bdaULByyiwUDu3GUAlZOJT0syJVFLa016fY0nIB4xc/jMa6lg464C1o4sK4Sr1OQoB00LU9nphk6B50e8Eea+mejre9i5c6B5k7ItaOn/SStgsjY2HwbrHqAmGqLGnZsuUgW+AHvKZ1C16yEAfJOWcsSkpZ7tu2HH9sLHtNyJiNPHrI4GWScteSXtceLTwsECXbSUQuTub6hRLQUYbLCg403p3zXTcy0KA1hBB3Rv9eKWC0SgZeC5u8AoMNkum1k7dL7d6z9XxlQJp/pdLSugbXDLUEUkkDP1RY6b6EDXt6e93GtiVmP8wN+RGYqfmV9x8+5utnb2ZBQ7bFIVu7vyZ17OOV/DlKmiLMAZC9JtuLitikjQl2dajGzZTZv0+yIE6EnFgJ02vylXJl8wMzYsD4VciN0Y0JEqsCPCPd+e+2xGfZzNg1jTVUErQf74+AY++5vHaSwPc8P5y5nREDcn9unfw+1fNtazGSfBGZdDRWuxxVWUDCqiEVZ84se89veVzP7HJXTd8ia+teZznPXWD5hrWVEUsjvV3qQOKRzlDLL7SWbbSVVlTJqSv5PvUhMN0dWbpLkiXLizJQLVU5niXZZtSXCYVhdjWl2++Y9yt0lawfyHLB+Be9RAHUXLx6JJJmmWJWa0Pl3cM5G1h4zJYsWid9qpRPONbPuDJGadSe8LW9jWejzMqM8p4rqmlQWzlIBsC5pnVXzpO9j98ra81XE7kWWFFLR86fEPhOy5v7Lxuq42LzIfLwMoaK4rbGQwC4hbl7Iao3QPh6nHFk7OM4Dy6TajWyJR1gDBAax5zgarZ+VeA4OZITPnfMsse9aige/hoZJ9i0yri7G90ygy3vZ348XyYVmSaUE7wGmaJlUPcSDGF0QAX38X/YEIxI1lPNvtE4BZpw5+zTondVZjZp9jf6/ZLhL0mfn+ggWeZV7aVw0tmVEh8liY5zSXM4eBE46o2aWEsG2b//3bC3zyhkdZ2FrBTR8/khn1MXjhNvjx8fDbD0AgCu+60cSbqXKmlDCTj/0gwY/fgx1v5rPbvsjdV5zPV3+/hp37Bh75UpRDglQc0VA7QOneV44iMMA2lghtdZXGilU9bejyxeqHZMnIPFxaRtumcFzPEBWL+niYHdWLTKd9CDEoSyZXcVhbFVXRYDpBgevymOV+6Y1LmVRdlul2VMCtKekvy2sZqYoGWTalmnkt6dg+Y310FSknhbhTh7pYevLxfIkUVk6rYXZj+aCTmB9wMrBaZxJvO1/ylWFQ6DxjrKcrp9VyhMc9Nj+emLHhEq1JdehTuGnsh+CiZufX4YfHKCnL2QrFcIg7gzwV4UCq3m5CuewsrAPjaYhgpjwjjW0blGhNyhFs0EvAF0i5fhdiUVsl7TVRZmUNCjdVmO0m10RNHzpSmW/zTOKNeeeCGzK+kWVUVwtaidDd18/Fv32CPz6+gXMWt3DZWbMJPfc7uPc7sOUZKG+Fs6+EBW/TiaeVCYOvbgY1n7qbrps/zwcfvYZXH/0n//r4hRx9wlm8Z8Xk/KNjinIoUN4KtbvS6ZwdvLEXXty++syGODMqKqFzGPGdgTKYc+bwZayeAusfGf52Dl4FbV5LBZVdTt2G2JldPqWaxOQqKOTCORRiddBxZkGLIJAxLQAzTjKupXkYqN/oTf990pxGYzna+4ZZ4LyzfY41yVUG87pvYZS2fIpbQUka5kGiB+JNA2yThzJHabJHlu2PYNS4mg3irprjDpiP0e7418827pj5EsukDulkECQzY2lhhhGDlm9LXyAnK2A2U2qjPL9pZJkcKyIBFp7yIQL9XSlX5tmNcVqrI5mZvwdBxErHkGUl/lk9qy5llRttfE5WyETyAAcMMNbnhZNyla94ODBqFsshM8A1OBCqoJUAW/Z289HrHuHRdbv4/IltnF92N/KDd8Pu16GuA87+Icw/d8AXjKKULIEwkbO+DfPPovn3n+DavV/i2r/cy5sf+ACfPmMJx86q1/g0ZUwRkQuBfwOagKeBf7Ft++4hbLcKuBN4zrbteaMqlGVB04KMRQN1HNx7JBLw4e8dosIyGvfVrFNTE/UOF6+CNq0uBpvcecGGmMXMEoKjESziH9g9KcMqEB7BPEdZRFwLp+t257g4uUdxYwZHPEDlD0HNNJNpDkxnPCOZxRBxFavB3MUKMe34kW2Xj9Q1MYj5ZDjzuxboGLdVl7FuR268Yr5MnpkFhpnF0YNliVH+e/cNfIwDJOD3gT894GBZkt99egBOmdcELzvXRpZBIB4OpCx1o43PryqJF22NIvPPdTu54PpHsLq289fDHmPGmhugaye0rYTTvwXTT9QEIMrBwdRjCH7ifuzbv8L7HrqKM/c9yH9f91aumXwOF586N+9ol6IcKCLyNuA7wIXAPc73LSIyx7btdQNsVwX8DLgdGOch11zypoMYcgKGAzhwMDpwXM4AJK1AfhFHK3ZqlBizhAF9jpXTcTdzz13B2LLh0HzYge8jUgX1c6BihJf3IIrvqDPn7FEZdFg0qZIFren3zai6OGZZXxe3VaWnughEBnW5HFRJHA8y4uXGz2PL58ZqHYwDttOOG3YcmypoReSGh9Zx9R/+zsWRW3hz8O9Yz3bDrNNh1b+YWeYV5WAjFENO+29Y+DYqb7mEr7/xY17Y8Fe+cuU7iXecwGdOnp3pbqQoB86ngWtt277a+X+RiJwCXABcMsB21wA/xag3546tiIPjWnnsYcXoFK+jk4hUs98qkAykRBQ0nyX0J+2xi6txExBETRbmmQ1x1ry6IzNBSbFpmFNsCRyGEIM2QlexnCOJ4J3GL6WgDb5l4VU+v+m3RTMTiAw5SUZKtmEVHxtGMUnIsLB8NFdEiMYOwmRiI4hhUwWtCPQk+vnRr/7A5Oeu5q+BB7CSPmTB2+DIT5pJ8RTlYKdlCdaHboWnf8/0v/4H1+++jMde+i2XPXc2tYvexEUnzBj+HDCKkoWIBIElwP9krboNWDnAdhcCDcBXgS+OmYDDwO24mQR/B5hWfRzY33oU9qa9+S0CJdELBb9l0Z/sH1FeiiFRNdl0zEKmw9lSGaF5YfPIXbqnHVc4W+FEx7U8DZI+fSwolJI9heU37T7YeXMTkxwAQ7kygmMdu+21mo3nYIpYNFdGIDDOltkSRRW08cS22fbkbbz+56/zyd5/0hMsQ5Z9HFlx4cjSDivKREYE5p2DNft0ePR65t99Odfs+SZPPfVbLn/8VPzzz+Gjx3UwtVBKb0UZnFrAB2zOWr4ZOCHfBiIyH/gScIRt2/2DdaZF5CPARwDa2g68g1b4OO6vYWgTeebfGXPaVkBvJ9OqY3T19jO1bmTukePB/NYKHl23k+BgSUgORJ8MZVoDDije9kAyyZU6ZdUmKU3VlMHLjjJpF8dC01CUhsUXTAKawtk9RwnvXInjOZhSQu08EAtbK9NxpmOIKmjjQX8CnrmJ3X/7H2p3P4ttV/L8vH9l1hn/MrQUn4pyMOMPweEfwrf4vfDEr5h91+V8a+cP2P7M9fzyydVsmvEO3nHiKuY0H3jwvqIMhIiEgF8Bn7Vte+1QtrFt+yrgKoClS5eOmSbkWqKSwzmCq6CNNAnESHDimQLAYW1V43fcEdBSGRlksmNDPOSnNhZiTpM+g8YMkeFP6zBKTK+Psaerj0nVBa4FX6Aolr18jIdiUDRcBW2kWUXHifba8Rl0UgVtLOndB/+8juT938favY5tySauq/gUZ77nX5lVX9ovLkUZd3wBOOzd+Be+E9beSez+H3HBS3/GWvtHHvzhbH5ccypTjn4nxyyYbuZ0UpTB2Qb0Y9wVvTQAm/KUbwI6gJ+IyE+cZRYgIpIATrNt+7axEnYgyiPmdW3SZVfCng0mff5AuEH3B6tb3DhhWcKR02sHL6hMSMIBHysHOr++ILBvXCzRbjzkUAYODjr2bzffiZ7iylEiqII2FnRuhYd+BA9dDd27eEI6+H7fZ+g4+q1cdMIsnftJUQbCsmDacYSmHQe71tH9yA3MXPNzlu+8nJ6bvsfdf1pK9+xzOPyEt1JbfRC7/CgHjG3bvSLyCHAi8BvPqhOBG/Nssh6Yn7XsQqf8m4FXx0DMIdFaVUY8FKCiLAB2x9AmT3UVtBIfkVaUksbNvtc/9oqDZQmnzGsc+zizwQhXQPfu4spwiKMK2miy4TGjlD35G+z+Xh6PHslXek6gs34xl52zgCWT1WqmKMOiso3w8Z8jfNzFJNY/ysY7r+WwV/5I5TMX0/30v/NEdAnScQYzjzqXUOUwJ2lVDhW+DVwnIg8B9wIfA5qBHwKIyM8AbNt+r23bfcBT3o1FZAvQY9t2xvJiUFHmZP8TGVo8UsqCpgqaooyY2pnQuRnC4xOSEvKXgBvjtOP0uVFkVEE7UBI98Mwf4KGr4I2HsQNRHq89nUs2HsXLu5v41EkzOP+oqYMHISuKUhgR/K2LaX/3Yuj/Nusf/xtvPHAjbVvuoOmRL5B85Iusjcylb+rxtB1+BuG2pTp/oAKAbdu/EpEa4AsYF8anMK6KrzlFxi6zR7FxFbSymuLKoSgTmXgDzC/6TBvji+Ub3xT7Sg6qoI2ULc/B4zfAYz+HfVvpr5rKfdM+y+denseG14KcsaCJK0+aNW7BhIpyyODz07L4FFoWn0Ii0c8jj9zD1od/T9u2O5nz9Hfg6e+w1ypnR8ORlM87maoFpxp3MOWQxbbtHwA/KLBu9SDbXgpcOupCjQciMP2EEU80rSiKohQHVdCGw54N8MwfjWK28TFs8bG7dTW/rD6Vy9c207MRjp9dz9UnzWRuc0WxpVWUgx6/38eS5cfA8mPo60/y8LMv8Pqamyl7/R8s2XAfVRtvgb/+CxtCU+lsWkFlx7HUzTsWiWrAv3KIoJmCFUWZCIgFdrLYUpQMqqANhG3Djlfg+ZuNYvbGQwB0Vs3lntZPccXWRTz1YohYyM/bDm/hncvbmN2oaXgVpRgEfBaHz5vN4fNmY9v/ygub9nDf4/fR/8LttO64n/lrf0Pk1Z/DLbA+MJltNUvxTV1F0/wTqGk6eL3cFEVRFKXksXzQrwqaiypo2ezZCK8/AK/cSfKlO7B2rwNgY9lM7oi+l+t2L+S5jU2EAxarptfx3hMbOH1+E9GQNqWilAoiwqymCmY1nQqnnIpt27y4cQevPH4PybX3ULfjYTo2/h+xTTfCfbCJWl4Lz2JP1XykdTFV05czbVIzlWXBYldFURRFUQ4BxnFS7AnAIa1VXHHrk1jbnqWl80km7XuKyfufoiaxBYBOyri3fw53J4/nzuRCtiQamd9SwVFzKvnMlBpWTa89uCcMVJSDCBFhZnMNM5vPAs4CYF9XN08/dT97X7iL8JbHadv7DE0b74WNwMPwerKOJ31tbItMoatiBlLfQbylg+bGOiZXl1EdDSKiLxRFGTLROnVhUhQlP5bPzFqpACD2MCbeW7p0qb1mzZoxFGcMsG0z+d2udcZdccuzsPU52PIM/TtexYd5WWyRGp71z2ZtZB4b4/PprJ5Ha005U2rLmFwTZVpdTDMxKspBjr1/B9teeIC9Lz9McvPTRHe/SG3P6wToS5XZbsd53a5jkzSwJ9JCd7QVq7yRYFULsdpWKuuaaaqK01QRJhzQQRwRecS27aXFlmM8mJDvSEVRlFKgew+sXwOtyyAUK7Y048JA78fSsqDZtvNJAs7vjO8k9HVD337o64JEF/Tuh+5dRglLfXaYhB67X4ddr5tyLuKDmmnQMA/f/POgvgNal1Jf0Uo9cExxaq4oSgkgZdXULTqNukWnpRf2J2DnWno3Ps2e9c/Rs+UV6na9xqTOdVR0P4S/ux+2A2tN8aQtbKOCl+xKdllVdAUqSATKSYYrsSNV+MqqCcZrCMZr8EerCUarCMcqiZZFiYYDxEJ+Qn4Ly1LrnKIoinKIEC43868pQDEUtKduhN99JFf5Gi18QYhUQ3kT1M2GGSdBxSSonARV7VAzHfyh0TueoigHNz4/1M4gWDuD2vlZ65L9sHcTdG6iZ+cG9m57g67tb5DYvZFY5yaqurYR6ttEpGsP0f37BjxMwrbYT5idhNlnR9hHmB4J0UeAhARIWAH6JUC/BElIgD4JkMCPLT5sBFss51sAAc//u0Or2e5vQEQQTPZ1Qcy357cl5hvgQ6umsE24nFAAACAASURBVHpW/Vi0qKIoiqIoAzD+ClrtTFj5SdMrQPJ8W57f5K4LlEEgkvkJV5qJOMtqzHwvGheiKMp4YPmgogUqWgi1LGHAoZ/+BHTvJrFvB527t7J/11b6OreT2L+b/u69JLv3Qs9e6O3E17ePisQ+fMkerP5efMl9+Ow+rGQfPrsXf7IPv53Ab/diOR4Hgo1VYLDrjbK5dIdaSNp22lEB8zuZBJuk+e1xeU/0j+LAmaIoiqIoQ2ZYMWgishV4bezEKWlqgW3FFmKCo2144GgbHjjahgfOcNpwsm3bdWMpTKkgInuB54stxyhzMN4vWqeJgdZpYqB1GjkF34/DUtAOZURkzaES6D5WaBseONqGB4624YGjbZifg7FdtE4TA63TxEDrNDEohTppWkJFURRFURRFUZQSQRU0RVEURVEURVGUEkEVtKFzVbEFOAjQNjxwtA0PHG3DA0fbMD8HY7tonSYGWqeJgdZpYlD0OmkMmqIoiqIoiqIoSomgFjRFURRFURRFUZQSQRU0RVEURVEURVGUEkEVNEVRFEVRFEVRlBJBFTQHEblQRNaKSLeIPCIiRw1xu1UikhCRp8ZaxlJnOG0oIqtFxM7zmT2eMpcaw70ORSQoIl9xtukRkXUi8snxkrcUGeZ1eG2B63DfeMpcaozgOnyniDwmIvtFZJOIXC8ijeMlb7EZ6fujGIjIJSLysIjsEZGtIvInEZmXVUZE5FIR2SAiXSJyp4jMzSpTJSLXichu53OdiFSOb21ycepni8gVnmUTsj4i0iQiP3XOU7eIPCMix3jWT6h6iYhPRP7Tc6+sFZGviojfU6ak6yQiR4vIH0VkvXOdvT9r/ajILyLzReQfzj7Wi8h/iIiMd51EJCAi3xCRJ0Rkn4hsFJFfiEhb1j5CIvI9EdnmlPujiLRmlWlznjf7nHLfFZHgeNcpT9kfOWU+W1J1sm37kP8AbwP6gPOBDuB7QCfQNsh2VcArwK3AU8Wux0RqQ2A1YANzgEbPx1fsukyUNnS2+R3wEHAi0A4sB1YXuy4TpQ2BiqzrrxF4GfhJsesygdrwSKAf+FdgCnAE8E/g9mLXpRTbq9gf5331AWAeMB/4PbAJqPaU+RywF3iLU+7XwAYg7ilzC/A0sML5PA38qch1OwJYCzwOXDGR6wNUOv2LnwHLnHvreKBjotYL+DywA3iT8746E9gJfHGi1Ak4DfgacC6wH3h/1voDlh8od+7JXzv7ONfZ52fGu06Yd+RfMc+5Wc61eDfwDOD3lLvSqeeJwGLgTuAxnD4d4AOedJYvdsptAL5XjPPkKXcu8CiwHvhs1rqi1mncb9BS/AAPAldnLXsRuGyQ7X4HfAm4FFXQhtWGpBW02mLLXiqfEbThScBubcORt2Ge7Y90rsuVxa7LRGlD4LPAa1nLPgB0FrsupdhepfYBYhgF+03OfwE2Av/uKRPBdBA/6vzvcO6TIz1lVjnLZhWpHhWYwZVjnQ7TFRO8Pl8D7h1g/YSrF/Bn4KdZy34K/Hki1gkzEPP+0T4nwAXAHiDiKfMFjBIh41mnAmXmOPLOd/5XAL3AuzxlJgFJ4GTn/6nO/0meMu8GuoHyYtQJmOy0aQfwKh4FrRTqdMi7ODqmyCXAbVmrbgNWDrDdhUAD8NWxk25iMNI2dFjjmMxvF5Fjx0TACcAI2/Bs4GHg0yLyhoi86JjXY2MoaslygNehy/nA07Zt3zeask0URtiG9wJNIvImx72nFng7cPPYSVoajNI1V2zimHCHnc7/KRhLcqpOtm13AXeRrtMKTKfHe5/cC+yjePW+Cvitbdt/z1o+UetzNvCgiPxKRLaIcSH+hMfNbSLW6x7gWHFCGURkDnAc6WfFRKyTl9GSfwVwt7Oty61AM8byWGzKnW/3mbEECJBZ79eBZ8ms07POcpdbgZCz/bjiuNXeAHzVtu1n8xQpep0OeQUNqMWYKTdnLd+MudFyEJH5GMvZu23b7h9b8SYEw25DzCjTBRg3gHOA54HbpYRjN8aYkbThVMzI20JMO34COAW4dmxELHlG0oYpRKQCOA+4evRFmzAMuw1t274fo5D9HDPiuBUzkvy+sROzZDiga65E+A7Gbed+578r90B1agS22s6QMYDzewtFqLeInA9Mx1gZsplw9XGYClyIcXM8GXOevg583Fk/Eev1DeA64BkR6cO49v3Utu0fOOsnYp28jJb8jQX24T1GUXAGpb6Fccl8w1nciLHCb8sqnl3v7Dptc7YrRp2+DGyzbfvKAuuLXif/4EUULyISAn6FMYWuLbY8ExXbtp/HKGUu94tIO/BvGP9mZXAsjJvBO23b3g0gIp8AbhWRBtu2sx8cysC8G9Om1xVbkImEMwr+PeA/MaOHTcA3gR8B7y2iaMogiMi3MYM8qybqYKOIzMK4A66ybbuv2PKMIhawxrbtS5z/j4rIDIyCdkXhzUqat2GeCe/EKGeLgO+IyFrbtq8pqmTKoDhWp+sx8ZFnFlmcESMiq4H3Y66/kkUtaGlttyFreQMmSDObJoy/6k/EZG9MAP8BzHX+nzSm0pYmw23DQjwIzBgtoSYYI2nDjcB6VzlzcE31bXnKH+wc6HV4PnCjbds7RluwCcRI2vAS4CHbtr9p2/YTtm3fihn5f092xquDkNF69o07InI58A7gONu2X/GscuUeqE6bgDpvVjnndz3jX+8VGEvm05538jHAhc7v7U65iVIfl42YRAxeniX9bJ9o5wnMwM3/2Lb9S9u2n7Rt+zrg25hnCEzMOnkZLfk3FdiH9xjjisclcAFwvG3b2z2rN2E8CWqzNsuud3adXA+E8a7TakxffqPnmTEZ+IaIuFbBotfpkFfQbNvuBR7BZF/xciKZPsIu6zGZrxZ5Pj8EXnJ+H3KxKyNow0IswryUDjlG2Ib3As1ZMWczne/XRlfC0udArkMRWYZxFT2U3RtH2oZlGCXFi/v/oH7HjOKzb1wRke+QVs6ey1q9FtO5ONFTPgwcRbpO92OSi6zwbLcCiDL+9b6J3HfyGuCXzu8XmFj1cbkXkzXPy0zSz/aJdp6g8LPCfU5MxDp5GS357weOcrZ1cTMEvjoWgg+EiAQwnmMLgGNt285WPh7BZLL11rsVY8zw1qkja9DuRKDH2X48+QGmLt5nxgbgckymVCiFOo1l5pSJ8sGY3XuBDzuN/x1MEOdkZ/3PgJ8NsP2laBbHYbUh8C+YIOgZwFzgMoy73jnFrssEasMY8DrwG6cNjwSeAn5T7LpMlDb0bPdj4IViy18KnxFch+/HvMguwMTNHIlJXvNIsetSCu1Vah/g+5gMcceROb1EzFPmc5gMsedg0nz/kvypwp8knSr8SYqcZt8j253kptmfUPUBDnfuq3/HxNe91anDxydqvTDx0W8Ap2OSXbwZE7P6rYlSJ8x71+3U78d4UC3CmVZjNOTHZBDc5Gw7z9nXHsYuzX7BOmFCoW7CGCcWk/nM8GaZvNI5tycAhwF/J39K+juc9Sc4+xyrNPsDnqc85V8lf5r9otVp3G/QUv1gXHJeJa35Hu1Zdydw5wDbXsohrqANtw2BizGpqLsw86LcDZxW7DoU+zPc6xAzwnqb8wBaj+l8xcdT5lL7jKAN45gO9cXFlr1UPiNow4swMSX7MVbwnwOtxa5HKbRXqX0wA2H5Ppd6yojzXtuISRn9D2Be1n6qMPEoe5zP9UBlsevnyHYnmQrahKwPRpF53JH5BeCTeNKsT7R6Oc/a/8VYAbswCVC+BoQnSp1ITxGU/bl2NOXHWIXvcvaxEZOYbkxS7A9UJ4wiXeiZ8X7PPkKYWOTtmPfAn/Ckn3fKtGGmWtjvlPsuECrGecpT/lVyFbSi1kmcAyiKoiiKoiiKoihF5qCOD1AURVEURVEURZlIqIKmKIqiKIqiKIpSIqiCpiiKoiiKoiiKUiKogqYoiqIoiqIoilIiqIKmKIqiKIqiKIpSIqiCpiiKoiiKoiiKUiKogqYoiqIoiqIoilIiqIKmKIqiKIqiKIpSIqiCpiiKoiiKoiiKUiKogqYoiqIoiqIoilIiqIKmKIqiKIqiKIpSIqiCphzyiMilImKLiH8U9rXa2Z/eW4qiKMqER9+RijL+6A2iKKPLauBL6L2lKIqiKNmsRt+RijIoeoMoiqIoiqIoiqKUCKqgKUqaDhH5u4jsF5GNIvIVrxuGiNSJyA9FZL2I9IjIcyLyEc/6SzEjgwB9jkuI7Vn/ZRH5p4jsEZFtInKHiBwxbrVTFEVRlJGj70hFGScO2J9YUQ4ibgL+H3AZcDLwRSAJXCoi5cA9QAS4FFjrlLlSREK2bX8P+DHQCnwIWAX0Z+2/BbgceAOIAu8G7hKRJbZtPzm2VVMURVGUA0LfkYoyTqiCpihprrZt++vO79ucF85nROR/gYuAycB827ZfdMr8TUQqgS+JyJW2bb8hIm846x60bTvh3blt2x92f4uID/gL8DTwYeBTY1ctRVEURTlg9B2pKOOEujgqSppfZ/3/JRAD5gGnAA8Ca0XE736AW4EaYM5gOxeRExz3kO1AAugDZgKzRrEOiqIoijIW6DtSUcYJtaApSprNBf63APXAdMwLIx81A+1YRBYDN2NeVh8CNmLcO34MhEcor6IoiqKMF/qOVJRxQhU0RUnTALyS9R9gPbAd2EJhN4vnB9n3WzAjgufYtp16gYlIFbBrRNIqiqIoyvih70hFGSdUQVOUNOcBX/f8fzvQCTyJ8YW/CFhn2/aWAfbR43xHgL2e5WWY0UBvxqrjgDZMMLWiKIqilDL6jlSUcUIVNEVJc76TMvhhTPapDwOX2ra9W0QuB94G3O38fh6TZWo2cJRt22c5+3jG+f6MiNwC9Nu2vQbz8voX4FoR+QnGr/6LmJFHRVEURSl19B2pKOOE2LY9eClFOYjxzM0yH/gecASwG7ga+JJt20mnXBXwH8DZGJ/7XZiX0I22bf+vU8YHfBd4K1CLucfEWXcR8GmgEXgKuAT4AoBt26vHvqaKoiiKMjz0Hako448qaIqiKIqiKIqiKCWCptlXFEVRFEVRFEUpEVRBUxRFURRFURRFKRFUQVMURVEURVEURSkRVEFTFEVRFEVRFEUpEYaVZr+2ttZub28fI1EURVGUg41HHnlkm23bdcWWYzzQd6SiKIoyVAZ6Pw5LQWtvb2fNmjWjI5WiKIpy0CMirxVbhvFC35GKoijKUBno/agujoqiKIqiKIqiKCWCKmiKoiiKoiiKoihjQKI/OexthuXiqCjFwrZtntm4h/tf3s7TG/bwytZOtu7tYW93AoB42E9zZYSWqgiTa6Ksml7L4rZK/D4dg1AURVEURVHGn1e2dvLk+t2cNKeRSNA35O1UQVNKmg27urj+gdf44+MbeGNnFwCN5WFmNMSYXh8nHjaX8J7uPtbv7OKf63by5yc28t3bXyQe9nPUjFrOXNjM8R0NBFRZUxRFURRFUcaJDbu6Adjfm1AFTZn4vL5jP5f/9QX+8PgGbNvm6Jl1fPL4GayaXktzZWTAbfd093HfS9u48/mt3PHcFm5+chN18RAXHDONdy5vIxwY+g2iKIqiKIqiKCNBxHzbw9xOFTSlpOju6+f7f3+JH/3jFUTg/Svb+cCR7bRWlWUWtG3Yuwm6dkIyAeEKKG8GX4DycIBT5jVxyrwm+pM2/3hhC1fd9Qpf+fMz/Oiul7lw9XTesayNoF8taoqiKIqiKMrY4Ohn2MPU0FRBU0qGpzfs5pM3PMrLW/fx5sNauPiUWTRVeKxl3bvhqd/Bi7fBa/dB967MHfhC0LQQph8Pc86C+g58lnDc7AaOm93AfS9v43//+iJf+uPTXPfAa1x2znwOb68e30oqiqIoiqIohxT2MG1oqqApJcHPH3yNL//xGaqiAX76wWUcM9Mzb9/eTXD3t+DR66FvP1S2wZwzoWE+xOpAfEZZ2/YCrHsA7vw63HkZTFoOR30GZpwEIqycVsuKqTXc8dwW/uMPT3Pej+7nomOn86kTZuKzpLBwiqIoStHpT9q8vmM/7bXRYouiKIoyNFImtOFtpgqaUlQS/Um+8udn+Nn9r7F6Vh3fPm8R1dGgWZlMwkNXwe1fhv5eWPB2OPyD0Lw47dSbj84t8MSv4KGr4RfnweQj4YQvw6TDERGO72hgxbQavvSHp/nuHS/x4NodfPcdh9FQHh6fSiuKoijD5tmNe3h5aydBvzVoLLKiKEopII6GNtwYNA3CUYpGd18/H7v+n/zs/tf46NFTueZ9h6eVs52vwc/OhL98zihYn3gYzv4+tCwZWDkDiNXDyovgE2vgtP8xlrVrToDfXwBdxi2yLOjnm29dyLfPW8gTb+zmtO/czYOvbB/jGiuKoigjpdeZS6g/OdyujqIoxWBfTwJ7uMFXBxmpJCHDbAZV0JSi0NXbzwd+8jB/e3YzXzlrLpec1pF2M3z2T3DlStjwGJz5PXjXb6B66vAP4g/CsvPhk4/Bqk8bq9qVK+Gl21NFzlncyp8uWkVlWYD3XPMQf3p8wyjVUFEURRlNDvF+njIB6O7rZ932/cUWoyTo7Enwt2c38/zmvcUWpaikPRyH9wBTBU0Zd/r6k1z480d4YO12vn3eQt67ot2ssG24+9vwq3dD3Wy48D5Y/N7BLWaDEYrBCV+CD/8VgjG4/hy4+WJI9AAwvT7GjResZOGkCi664VGuvuuVQ37ER1GUiUtvInmQWpkOxjopBxP3v7KdR1/fSU+iv9iiFJ2uXtMG2zt7iyxJcZER9mFVQVPGlWTS5rO/eZy/P7+Vr549j3MWt5oViR646QITbzbvXHj//5lkIKNJyxL46F1wxIXw0I/gJ6fCrnUAVJYFue5DyzltfiP/dfOz/Nf/PatKmqIoE5JbntrIfS9vK7YYY8aBjtkp48+r2/bxl6c2FluMMaenTxUzJRN1cVRKHtu2ufRPT/OHxzbwbyfP4l3LJ5sVfd3wy3fB4zfA6s/DW34MgTFK2BEIwymXwXk/g20vwo+Ohhf/CkA44OOKdyzmfSsm8+N71vJVVdIURZmg7Nh38I1au4/jkY5IK8Xj8Td20ZNIkjwoLbtptMuQy6F+t44wiaMqaMr4cdVdr/Cz+1/jI0dP5cLV08zCvi745Tvgpb/Cm74Dqz83PsOjc86Cj9wJ5S3w83Phjq9Csh/LEi49cy7vWzGZa+5Zy2W3PKdKmqKUMCJyoYisFZFuEXlERI4apPwxTrluEXlFRD42QNlLRMQWkStGX/IJRs9e2PRUUUXQJ/HExY0xT0xABW3znm7+8Nh6OnsSg5Y94NrZNuw5OGLhhxtzdbCz5tUdwyqvCpoyLtz5/Ba+/pfnOH1+E5ecOtuMgPbuh1+8DV7+O5x5BSx5//gKVTMNPvw3WPRuuOubcN2boXMrIkZJe88Rk7nqrlf4xl+eVyVNUUoQEXkb8B3ga8BhwH3ALSKS1z9aRKYANzvlDgMuA74nIm/JU/YI4CPAE2Mj/dgwZs+qV++Brc+ZQbUic6iPyE9E/I6CNhFjI9/YaZJ+7ByGVXrEt+G2F+G1+2DX6+ll3bth20sj3GEJcIjfsCO1OaiCpow5a7ft45M3PMrsxnK++dYFRjlL9JpkIGvvgrN/AIvfUxzhAhGTvv/MK+D1B+FHR8G6BxARvnLWXN61vI0f/uNlfviPV4ojn6IoA/Fp4Frbtq+2bftZ27YvAjYCFxQo/zFgg23bFznlrwZ+CnzWW0hEKoCfAx8Edo6d+KPPmPV/k4NbD8YaHScbJ/pH/1xb4lrQkqO+7/FiKB3tA75GezvNt5PEDDCD2Bsfm3g3wAQTd+zQJCFKCdLZk+AjP1uDzxKues8SyoJ+MwH1TR+Dl283bo2L3llsMY2C+KG/gj8M154O938fAf7zrHmcubCZb/zlOX718LpiS6koioOIBIElwG1Zq24DVhbYbEWe8rcCS0Uk4Fl2FfBb27b/PhqyjifJidaJGwEagjaGdG6FZ26CvZtHdbeui+OEio1c/0947f5h6UWuW9+o3oa2k3ikv28Udzp+yCFuQlMLmlJy2LbNxb99nFe27eP771rMpOoy89S65WJ46kY44VJY8r5ii5mmaYGJS5t5Ctz6efj1e7B6dvE/b13I0TPruOR3T3Lr05uKLaWiKIZawAdk9yQ3A40FtmksUN7v7A8ROR+YDnxhKEKIyEdEZI2IrNm6devQJN+/Y9Q7wC4T0YVsqLjum4N2+PZsgFfvHQeJDkL2bc38HiX6+s25e+z1XaO63zFlxyuwZ33q71CS07iK2ajGX1l+810CVmxl+Iw0MY4qaMqY8YuH1nHzk5u4+ORZrJxWaxb+4xvw/7P35nGWVOXd+PdU3b379r7N9OwrDDsMKCAC7oqgcUEREUnUn8GgSfTNavIm0bzmzeJrjBqiCaIibrggIAKyMwMDw+z7Pj29d9/uu+9V5/fHqVN1Ti333u7poQemvp8PTN9bVafOObXc53ue5/k+L30HuOIO4Mo/nt8OuiHaBnzoHuCtXwL2Pwz855UIndiAOz96Mc5f1IY7frQVm44k5ruXPnz4OAUghKwFy2f7CKW0oeVqSum3KaXrKaXru7u7GzvRseeAY8/OvqM1+yN/3jWUws7B1Ck51yuNhs2c4xuBzGtf0v2U4BS5J3tawgCARe2xU9L+6YaT9qCJ14Go7F/91eVBO5VLRS8fn8L924bq73gaIBJUZ3WcT9B8nBLsH83gHx7Yg6tWd+GTV61gX276NvDUV4ALb2YE6HSNUyEEuPKzVsjj965H7Okv4bsfPQ9LOmL4xPc2Y89wer576cPHmY5JABqAXtv3vQC8XN2jHvtXjfYuB/Ok7SaEVAkhVQBXA7jd+Byek55rRpiXPvc1kzSbZXh4Iosjk9mTb/g0Cp1s+KfjNOrzmY6Qqkj/vpowk7uI2v49WYykCtC4qX4K3henElZZjLlve3B6DsWKyjmWetMIDj4GjO2eUfNB454PKDO79199T4qP0x7FioY7frQF8UgA/3bjBVAUAuy5n4U2rn0XcP3XT19yJqL/YlbY+uJbgA1fQ/v3r8WP31pGcySAj931Ik5M5ee7hz58nLGglJYBvAzgrbZNbwVTaXTD8x77bzY8Zr8CcB6AC4X/NgP4sfH33CbQnAKDS9eqaJ/aDkUr1d95NphH0mMafDM9wMe845SE/r0CKFd1DCcZGWjkvuNhuHOhppopVvDi0SkcmTKe5VdtDtppDF1j0VJDLze2fzEFjO+d0Slme8/7BM3HnONLD+7BgbEs/u3GC9ETjwCDm4FffApYdCnwgbsANTDfXWwc4Wbghv8AbvkloGvo+vkH8Miye9FaTeDWu158dSU8+/Dx2sNXAXycEPIJQsjZhJB/B7AQwJ0AQAj5PiHk+8L+dwLoJ4R8zdj/EwA+DuBfAYBSmqSU7hL/A5ADMGV8nlvrkp6CFfHkCcTyg2hN7QMtTKMpe2yOTzCPBO1VZtybKOeBnfcBuVdTePwc3+pGe6+2FMmjs/Q+z36Y1pE8by/HedkrkIP2ihUSL2XZf/ONohH+nTx+yk4x28UJn6D5mFM8uX8cP9w0gE9etRxXr+kGpo8DP/ow0NwL3PQjJmv/asTKNwG3Pw9c9Xm0HLwfjwb+GO9N3YPb734WhfKrK+zAh4/XCiilPwHwx2CCHtsAvAHAuyil/Nd2ifEf3/8ogHcBeKOx/18D+Cyl9OevZL9NnAIPGuEr+ISAHvwd2pIzC8fxBrcyTgMLW1ySH3wZOPKUx46nQV8BIGsIwkwfnd9+uEDTKXYNpVDRTpH8va4DxzZALTFDeEYqo9kJpqQ4j5gtX+HD1HSKrQPTKFdnPr98PShXMRo7xTlo45kiHtgxPGcLzzUJyYHfsv/mG4efOHVtH3gEOPS7WR/uEzQfc4ZUvoK/+PkOrOltxhfevhYoJIF7b2T5Fjf/DGjqmu8unhyCUeDNfwt8ZhPU1W/BZ9Wf4d/Hfx+/uvNvUC2eBitBPnycgaCUfotSuoxSGqaUXkIpfUbYdg2l9Brb/k9TSi829l9OKb2zTvvXUEr/6NR0fu4JGjXbJHNbtNoMr5pH0uOW4DN9FMhNeuzfWF8rmo5S1f1aUEqxezjlub0xePRj969YhMkcIFeqzsr7cTyRw+GJLA6MZeakHw4Uk0BmBNHxrQBmGPp39GmmpOgCSim2n0giW3rllA29MjM0nToJrjHM44kcBqby2D868/nlM6VzkZBTpPzKMZ5moZRTubkNj25E/fK0QHZ8btsrZYBC0vKgUUaCi5XG3iU+QfMxZ/j7B3djMlvGv37wAoSJDvzsViBxiKkidq+d7+7NHTpXAh/6AfD7jwAdK3DT1DdR/JdzQJ/5N8td7sOHDx/1MFMPWn6qbpicaQwQZe6cXZXGEvKHkwUMJE5dbu7Mh9PYEU/vn8Dv9rgbZ+OZEg6NZ7FjTpQwbYaqXkV58gimT9JjUapq+N3eMewc8u6jl1Gov8KO0fwcRZykC1UcS+Tw0rGp2jsObDopL0Yj0/LMgQn8Zmdt1dDZhOdaz7JB0FInZtzG7FCbUFFKG/IIng7Odo7hZAH3bxuq7Sk++oz3NrBxn0ydSQrg+cMJbDzssaBkg0/QfMwJHtszhl9sGcLt16zE+f2twIN/wsJOrv86sPyN8929U4Mlr0fv557EvevuxEvlpSBP/APw/84Ffvf3QMavl+bDh486mClBO/wEcKR27WxKuQFCMGdBawWhdlUNA+WlY1PYemJ6rs7qiYZNpAaNqVy5iqqHipsYqjZr1OjHvpE0njl4cjXHqkau0kTG3fNxYCyDR3aPNhiOf2q8HXwGpnLlmYdTus0f72a9y5I6we7fU8gW0kVn6CEnZCfjPTJJHTkFpnpyAEgcntWhOwZTeHjXCEZTRQDAaKpo/u2G08GBxj3EuZPwuD6+dxxbBoz3W7rxMh5m8XJdB9EryBQbGsegSgAAIABJREFU64NP0HycNKZzZfzVL3firL447njTamDD14CtPwDe+L+Ai26e7+6dctz0wQ/jgfO+jutK/wfH2l4HPPf/gK+dB9z/mRmr/fjw4eNMwqkwGg1jYC5DHKXIgPptJvPluRcbKOfQNLkDoDMx7k++DwQ6guXU3Nj3LoZq2SArc60/I2LIUCGcTR7UbJA1wi1HU0W8eGwKOqXS+GbshXDZ32H0axWgWjJ2d2l/tgIbQlt1C6SLp7N1YTaX11ozoChWNGihuLxDKQuMbJ9d4ydeBIa3zkqo41giBwDYdDRh/sv/FnEaOdC8MQP2mCsL99DxDTUX4pP5sum15penY2orFg4/2vD5fILm46Txj7/Zi+lcGf924wUI7b8f+N3fAee+H7j2r+e7a68ICCH4v+8/HwvOeh2uOX4bfvumh4CLbwV2/hz41uuBH36Quc5PJ3+/Dx8+5h+n4p3AvXKEnFQ4jgRNCMFza7OYBp22VNCePjCBXcNzHO49tAWRzDGES4lX9FUaHHkZPePPgZyqsgUGTsZDV+9I7mFTVW9jtDoXjAIslPJxI9xy09EEJrMlDBgGfUNN6zoTfqkIHhmXubccaEZjBx8F9j4ASil+vX0Yu+33X3p2RY1P6a1WTAMp736Zzy+l2DWcwp4RWx7biReAyYMsz2+2OL6BnUunCE0dhFqd+xDl08CBZoKT7FShwsRQ2pY59klkS9g70kCt26r3O8HtHRgtNO51A3yC5uMksfHQJO57eRCfeuMKnKMdAH75aWDx64D3fOv08Gu/QgiqCr7xkYtw5apO3P5wEr9d+gXgT/cA136RrVJ973rg21cD+37jEzUfPnzMHKM7G9uPqzhCwe7hBoyMhtoUQ+Nc3l8HH4U+sEn6aipXZsb26M65qd+ksDwcMhNPiMu79thkbkYhdipXYBQ9d9nxOZcIz80iN+vgWAapTH2DutrAeI/bSNRswed2MmsZr5MzybFLDzHhl5Ht1nf7HmIheQJ46KB5iY08SS5Nf3TSNp45EmMxUSkgVahg36j7M8a9eDWtoIOPAgPP2w60/rST9mzJ/hwZrXuG51IcHMvUvv7G4stvthxC+vgWdCY2u5puVU3HcwcnkcrXfpY1nZqCOp5e4UaLQtuP2fULYKq+EupEpoSRVO282af2j+PZgxNwe589d2hyTkVzYiPyu7FRG9AnaD5mjWJFw1/9cieWdsbw2fURJqcfXwB8+F4gGJnv7r3iiARVfPuW9bhgcRs++6OteHKgClz9v4A/3sVqqZWywI9vAr7zJuDQ4z5R8+HjTAGvg+VQYWvwHVDOAxP7G9rVVHEUrayTfdc0kCunuTlgUgOs342SSxHlnCyIogSgU4BQfQaCC/J+6WIF2weTePm4e56ca1im7kIujj4zS4lwb3P9hSON1UjTdWoa7geOD+Lg0/eAGOIRXmuiFX3uiic3CqsvNiKFeiGOHtsyY65CJ/amOEHUdIodg0lQnr/Vtbp+p+vAHNPkIWDfQ3h+zxFPdUa7VL19VJuOJDzvQw7dJHkeSi7GooWXGuxwqog9I2nstXvepI4Z5zAWIIhHCHEiV0YiV8KeOp6l5w8n8Ntdcuif476cjXqtXmWLJMO2sgsHHwP2s2fxxFQe5aqOjYcn8eJRWTxm1nf+0MvArl+4E1NxYPkpYHwf+zt5QhpjMDdqu3aNEVSfoPmYNb7xxCEcS+TxT9ctR+SnH2GrpB/56atfTv8k0BQO4O6PX4Y1fc341A8249Hdo4ysXvwx4DMvAjd8A8hNAPe8D/juu4Djz9dv1IcPH69uFAxDbHyP/L2HoTqdK+P+bUOCul/98LNcqYqxdNEkU80ZWZ78pWNTDklySqksLFEpMo+/fYVbJGgefbaTGwpqeZ1mQwz2PywLoigqKKVQqIcHze0ctu+4OTWWdhc0qEkchG1egiKexzVQBNdBPsp5ad4rmo5tJ5J4cv84HtwxDAAIVYwQKiMXJluq4pkDEw4iVpuY2baRRtU3GmrNFc5oyvpHDSfzeGT3KFIF2VC2H1mpWvfH0ckcKiTEPijBBnrWIAyvqlIxvJdUR6gkk609I2nky97e3tF0ERQUx8RC2FNHpFp5lgfNY364uqPHAgq/koVasu6c5JnncGf5/P6MBGXaYL92iUYk+mvkkWo6RSLr0obXu6SYQi6TxHSujC0D09h8vLaqp+MZr3fvTR0FqI5k3m1cQp7v4SeAsV2s5MeJTWhLWu96CqAj8bJ1VIN5tD5B8zEr7B/N4M6nD+P9F/Xh8m1/DkzsA268G+heM99dm3e0xoL44Sdej3ULW3H7D7fgYS6/qwaAi28B7ngZeNe/spfxd9/BwkKzJ6fi5cOHj9MTrD6VYSCZxpABjx/qpGGEHuVhZ/b9XI773d4x5oUxzmUnMsPJgiOM7eB4FhsPT2I8YxCW4a1M2S07hs3HpqwwIXHFe3gLsOd+x/l1SiVjR9cxt1ECSgCUAoRqM2jWThqBcHEC/YMPoZDLoqrpNvEKZwvE9ACxOU8VKth2IsmMyAbqUpUmj6CaMWS1XVxc0SC7J3ritqiT/b8BBl4wPx6eyOJ4Ile37td0vmzmkw0nCxLxc5s2ccwnpVRpQy1BDXHOD09k8evtw1adOY+Lm8oxMpQpVqTFADtBqJRk8m1tn+HYhre69Nv8S2q7NbUP3RMbHWV2dFo/00MK/xSLchNiXRuvcEklYGx3J2BBlZn4riGO/NiWfukcXrPEPZNBVcHCod+iKXsMQO1C3ny+AsWEtUgF1CRoOwaTeO7QJA7aQwxtYwxUMugdfQoAsHfUUkJ1Uyo9PJFF2ninml5JvWL0wzYAl8WXVKGMg0MuZTgIwa+3D2OzWOrBGFugKr9ro0XrXUH8EEcfpwq6TvGXv9iBeCSALzf/goV6vPP/AivfNN9dO23QGg3inj+4DBcsbsMf/Wgr7t8mJAIHwsBlnwQ+uxW46vMs9OkblwCb7/LDHn34eLWjWjKf42KF1ac6MGz8gNtX8QeeBzSnwR1QOCngoU01PFp26G45Iu7vFS45XSwb7Rv5KJQQDCULVpiQmPdVSCKRyjo8PsxQ04XPwjkzI42VFKiWmZHqMidQQ6AAFL0MUsk522vAgwYAzVnmzXpmx348vGtUMjDN0Mmd91k1kQj/h23jhl6qWAHKWSOcyeO9nZvEhr0nsG3QW8RB5dcaFIPTeewaSlntZSxRAbvhKRIT0xAup9E/+BD0zBiqmo6Xjk3h+Tqhk+J1akgYoQ4a+QkT53xgihGvYqWOV8GQNX/5+DR+u3vU6XUzQhlJXl7snLVQzgwk6IMVY95sohHyNarfj7Km41giZ/ZZdxAzjxBHj7xM49YylULljQHpoxlGSRRXas27r4AtkrQldwNozJscH97A0jo4arwLuId0z0ia7cdPbDsmnj7kIEGAjTCO7gT2/Jo9U8L2RLaEhcOPomPKScJFDya/ZgfHsyiVvfMoh5IFaLqOoWQeukGrSM28XZ+g+ThF+OGLA9gykMR3zt+P6EvfAC79BCMcPiTEI0F8//cvw6XL2vG5H2/Dfz8rhxwhFAPe/LfAH24A+s5nteN+8Hs1VZ18+PBxGoPqwN4HWEQBrFXnZNYwJOweNMCVUFm2HBcBsJMRHSem8njmgGGMTh9HKw+pqSHIUbUnihkYtnnKSho7r1nDSTh/WdNxNJFz5HjoOkXf6NNQq6wtyVCqFoHRHZ79MjG2i0UWGDlVkjw7UaFTClUrIXz4UVN9biaQbWSmcika8KlMHqkJ4/2bHbcdaxjLYgTg2C7gxCYzhDFTrFhhbfkp4MhTaDY8DfycbMdR4MjTbIxmfhgjH4cnstA04XpPHgQyo456WuJYOLEMl41rMroT1BDVEOs+1eOwphfLA7pOsfHwJJJ5D2O1mAbJG4TQZuVL5zb+HkoWTMLrsFmF8RYrmiRxXtF0c3fzsHCL0UkPIjtDojaVKzsIq0ngzbwtDYGytY+dhHl6l8o5BCpOcnFiKo/JbInlOw1tQeTYE+aZXcfA59ptQcM6CrmShpePT9k8pPbFH+5BY/M+kipI+2senshZ8d9GQvwoBXb/knmSd/1cVpIFPGvDSYR8Yr/jOAqKjYfYsx0t2HPD6vTHAeseHUoWMZIqYiTDzldLzMgPcfRxSjCaKuKfH96H3188ikt2/D2w4hrgHf803906bdEUDuDu2y7DdectwJcf2ot/eGCPMxG9ey1w6wPAdV9lP/bfuhzY/pP56bAPHz5mD0NJTgrngbCaSlwImst6NTcyFJMM2EMcNWwZmMZ0vsxqWw2+hOassfLrakiw744lcpI3nxv9Zk6WYdxyh1rICJESz8+NUKcHjULVCogYoTwOj0HFmfc1OJ3H0wcEj0fJCGsKsHC/LQPTeMrczsiawkU7svaQI+9x19pFNOgOvPw4Dm56yPUYVw8IJ8OGgfzEvnE8tscIZcobZMmYO7OYMaXA8Y1AbgIDU3nkK8xLIBGlsjBXI9uBY89BtRM0aQzsXx46RfPTrM4VbGGLFOwaCyRGPK9CSE2DNVOqYiJTwtYTHh7Bg48icOwp101yf9knKTTMZU+dMq9iLeLoSCmyeXTsYYmuyE44iN2RySxy5WrNEL6Oqa3oHX/WbNuZ3kTdQz33P4zesaccX5vrIZwA8pBJt2uSHmZCOoCH19xCVdcxOF2wQpmFNrMjBzCZTFlhd4RgKlfGi0ensEdQgTXFUIS+RApjoIU65TQodc5AQwTF2KdSYOcsy6qplNiiDMzT1SZclAKKMV8UCrYNJqHpOnRKka9UATUk7ctBQM0vdg2lcGAsjUf2WGIoBWMBIaSwRR+Fuj9j0tjqwCdoPmaEv/v1bvRoo/jrzJdB2pcCH7wbUOcw+fY1iEhQxX/cdBFuu3IZ7tpwFH/0oy3OOGlCgEv/APj0c0DPWcAvP8UKXVdqS8X68OHjNAI3PNLDQC5hpd0Lq9SJbEle5R3b7WiGr1a7ebD4eaIBts0uRDCTBW2H4WScRzM8f6oiuov4Me5JNbzPmhp174cSQKGs4cSUJQv/8vFps6g1M6ycvbc8LNTIQROMm3rhVUafcqUqCmXN8IB4ewACFad0vqUYWWNmFcWZv2WsoOtqxOwDEoeYN8AYAzeYW9L7pXtCOfac2yls/RaJl9zHmjqX+x9mngnzCCEMD0yMg9ryCaUdBPxm5wh28PDNalnaJ13wJg1uYYf2HmeLVewdSWM0XcRk1umx8yJeunB/KFqxPhnQKsDRp62QVhvE0nFe5yTGc2Mfl3hP1HwuR3cC+SnTIOf+QfP9YfxFQNk9v/9hWW5er7peL0cUqMuzu280jR3bt0hniwxtQCw36CouQojVaGdiM5TDj6Eltc91nikFAlXnMzWSylsLFh4g9rw6R/s8NFiG+Bi63Wc6pVCNRR5dCSJTKCNbquJYIoc9w2mUhcUA25vC/KtY1ZAuVs0+tKT2o8iLwFNG9sT3VMKm6OnnoPmYczyyexTP7T6Cn7b8O1RowE0/AaLt892tVwUUheBv370OX7zubDy8axTv/8+NGJx2qV/TuRK47WHgqi8AW+8B/udtDdX98OHDx/yDiqFGqRMOg65QquC5Q5Nm3g0AKefB3Nuee2IPl6mW0T/0MPoHH0K1aDOAXH787QaBqxiEsErNBTGs8DA4clYAlheVTTBFQd1OEuxGvqLiuUOT2DIwzaIIhFy9B3YMY5MYMllykwWn0ClLvjeN+fQgAKZ6WaxU2btSfF8aRt7v9o7h0T2j9gbNYZt/u4zRvqNScsnTUgLO2mp8Do2P9hBFEZHiuGxMFp1eCbtxLXoe7VfT1D6wexdAWbipgXSxgkPjWQTLSShaGSem8tg3msbhiSyGp50heBTyfVnRdBydzOHhnSN4Zs8xz/E526m1kW3dOjBpEoRa9qy5jchfBCpZLBh5HJTnhXk1whc/8u65etTjbxHcWyJujxRGoWu1Q0bNLozvA45vhGIsiCQMQmp/pgAKVHLMcybkJ2JiPyP+jr7Xmmlx0UVeuAjlJ9A+vR2tg09KQjWAm8cKiGcO20J5gVS+AgqKYCXDLo2wkL/t+FTdOmMOEpOblM9rhDhaoh9lxNOHoGk6iG6fP36QhvCBBxDNDRptqGCeeSBTNBZUbIcUKuz7nvENaEnbS52w6xXPHDKff6pzb7jVkE6pVe6B7VRr6CZ8guajIWSKFfz9r3bgruY70VE4Btz4faBr1Xx361UFQgg+cdUK3HXrpTgxnccN39iA5w+7/CgoKvDmv2EEOHmcFbg+8tQr3l8fPnzMDPzHHADyhTymc2UoWglNaZZ/WjWMwXwtJT5KERzZavPm2KyGkmXAK0a+Fkc9UQS1moO+6+csX0i0+YWwTGeYEHXkfBQqGh7dM4p9zz/Izms6CTlBszWhBExvH60UgL0PIJ45xDZpZeSGdqNUpRjPFKGPbHeKD1AKChZGaeLEi6CU4vBkFs8dnGA1i4YsOWvYime7O4UEL4cRgmrOYd4ijeEsm+fw0cf5jEhjc7Ytf6F48zNz71ApYY6To1zVmdqk3cMk3EOmkWoYfjy3LlKsoTKp6xhIsIWCnvEN6JpgJV9UrYBkoYJDo84aXSJfF1HWdOQKZeQrVRdK4O7FYJt0xNMHEajkoAxvlYp/E72WyIL1Fd+SLFSwZWAaFYMU8fvESXLq90/uK1xvHLEQMtFlhcBgOYnOxMtQR7eZz5jZxORB9xMFwiYJ59fW0Xcvz6YX7B408R60tcPvHUWzhE4yqQRe3mHVMAxUsvIilABVk0OYNx6eZKfg59EqLLKgWjZDDF27TOX+mOCFysNx3mNp/7bkHrSk96M5fRALhx9j4Ze28Ufzo6BaBc0ZYxHHeKfJYcDys7dbCPOM20qXuN7buuZcnAJQDTSbfxM/xNHHXOJfH9mP2wp347LqZpB3/TPLPfMxK1x7Vg/u/8yVaI8F8dH/2YTvbTzmHje99h3Ap54G4guBe97PPGo+fPg4rTGVK6Oi6dhydBzbB5Nozh6DTpkAQFUInxnPFFnOAyD/mBdTCKSPoWNKkNy2GyuiHLdDFMTNgLO+i+WGoFU1IHVC8spQQcCEOnLeLII2xQUihD5nS1WcMCICeDiWI2RRWEGnZbZvpDAGolfQN/I4WlP7cGJ4mOVllTWXWllCn6jzT0eoJ6UoF+wiDxbMPBQxJIowD5ppGOuWpH80zYw63WV+h1NFQUTB7ACOTFiEQ7F50OzS54HCJLonXkA8c0g6w46hJA6MZWrb5c5Tg4KiJbUfoBqCZRaGWNGoIGevQyHE9DYEjVC0kLGvmEOD7ARw9BnzdypdqMjKxAAAHXuG0950RysjlhvgnQMAhEsJtKQPoHfsKeiJw6hMHjYHEylZHkI3h2+yUDbHCgDDySJ0SpEyBUw4M/LqEENF01hNMo8JZjnj4j3N8o2GkgJBM+5Nfk1NAlKxPOWxyR3Arl+wnEIA8bDlrdV1CgQiqAiLEqlC2Sx2LXmTqu41/IwOQtNttQ0FEOlYKj0z0cKo2XfZa0iRK1WhVnPoHXsaoYStlqMBRS9jWJiTsqbj4HiWkRF+7x/fCOz9NToTL3kOQdeZ8IqnkIYtj5f3VTGiDEIltqgSKU44Ln3H9Dbnu4NSHE3kXJUynV53l4Ur+zdUR0Wjjm0VkaD5IY4+5gpbB6ZRfPFufDLwEHDZp5hqo4+TworuZvzqM1fi2rXd+N+/3o0/u2+Hs1ApAHQsB/7gEWDZVSwn7fEv1c+78OHDx7zhyGQWhyey4AairoRQqmoYyxQxbohxFCo6BqbyOMAT70WlMaobj7gpfI1cqeqQyuYGhW5TKXOIENmg0CojIDbJf92+ikx1UNFIN4wsKzTb6s+0lGPhcX4hfNAkW0RBR2KruaJcrFLPMZSrgvHqmr8iH3NiOo8dg0npOFrOmxZ9+/R2KFpRPorIRn1Z0y2vEfcM2l6/iWwJOweTODQueDwnDgCFKYvMAo56WNsHLS8ooTqCReaxClYy0vkBMCGRhsC9lyzMqhJqQ/v0TvSMb4CilbDx8CR2mpLjFIoCqIbHRCdBhAMqqCkTLszx8FYmyiJ4WYnNC1JPmU6p5tE+vROR4gS0ahmP7B6VvKGHJrLYcGjS/WAXg3abIVTCPYsBI1mszMMiuYiE6H1ywd7hFAanvXOidErRGpFDX+1kWzHmau9gAsFySjqWI5w+irFU3iJd4vAAFHTV3AYwaXc7CCDlylU13bxHqrqOXXt3Yc+endh4eBKpAiNasdwA+gcfQiw3gPCh3zCSaAhviEW/m3IDxlicHrJSVTfvE7UgR/3w+VW1AjYfGUP/4EOI5lnYc75cbVix0OxHYhd6x591ldAfTRfx/BFbGQXjXcG9xfy+9MphkyIM3MKOZ+KhdAHVNVSqum2hyrEXC/Eu1i5r4RM0HzVRruq456c/xpeD30V1+bXA278y3116zSAeCeLbt6zHZ9+0Cj97eRAfuHOjlEBvItIK3Pwz4OKPAc/+K/DrOzxldX348DH/KAmkQFMsVbBQQDYazd9uMccsOwYKVlspn2FKahsPjVtiDByGcZHOF2VBBheDYOHwowgXmWGj6BXmkVADkn2ii8yDUvSMP4e+Ew9jMltCrlxxhDhKq8B2a5PD8BbYd+JKe5QQq4YUAF4FgII6DJuqkM8zlStj8/EpHE/kpP10SrF7OIV0sYJkns0JD5UMlaaR2X6/5JlZMPK4qwHFamxTPLF3FIcnmaHMw6D43nw0xaoGgMoesdEd0I0i1nw/e3UpMWQxUM2hKbnP3LJ3JIOD4xloDS7G5WwETjPyYCrBuEkYxNA1dhoKhRCLoKkhBBRiCVKIIYaxDgDA2BjLewqVprBw+FFECpaSpuWRtIfOUTQb3iICgs7ES1D2/hrFiob26Z3Svi56f8b3Vp9FRApjaB/bCFTLCBoeYL2UhlrNg5u3VY1Kocd2lCruuUccGqVWrTqT6/H7V/bmBIY2oWfcEnix31onpvM4MslqCMpeKqCKGvmP0p4WdgylzPfCRKaE4pHnUTr2gjEu5v3luWExgzSB6ixnDWJeJIWmhAEAVTXq9BNpVfPcPK+OX1O+b6CSM8McW1N7ES5Oon/wIYTK0/LrwY2wjO9j9QQBBEqGB1d3V31lYkEUuvFetYf+hipc+VKX8vx7xllZDvk6O2VTaIPhh8ZgHF/tGkyipGkgVENIVVyXqwjVgYOPAQcfrdm8T9B81MQPH9uIv8j8H5SbFyFw492A2shLxEejUBSCP33bWvzPresxkMjj3f/xHJ7c51KxXg0C138duOYvgW33APd93FEU04cPH6cHHIIRBuw/11wUwAxhzE9h9OBmc2U7Nz2Gg+MZuHml+KHDiQwOjDNPnKKVQQruYgc8hInQKkpVDVXYQoUEY4NSltxf0XRsODSJnYNJl7pDummgiPlVxNUkgTwGY7z2UJ+SQDQk8Q5KcWTCuaI+kS1ZhIkyslSoaDgwlrEIVZXNZbCSRrboNNSlHohzYNuq6dQIebSFLhmsMqha85MvVa3FNmOshyezssy5AAIizz+o6QHhmMwUHKGuvObcUT43RhsaNZcATOEThVZN7wIPP1UIoOgGQVNCRsiXcW0MQ7Wi6cjpzNs6NsnILfe2hEuWx4sX/XXLxdMp+16RHZQOBCsZYMRZL89+VTha0gcQLk0BpbTJhCPZQfSNPml60I4mciyPKDfhqorMc9YIwOrT7XvIsQAaEJQLtw5MY4fh/bQTSqvcAVd1dCecu4ZTMkGj1N2bA6Ape9xx3a3zeXt7qrqcy8g9o2VNx+YtLyJdKEm9L4U7WZtK0EFWg/vuR7iY4J1l35klONg/zFPGvlO1IromWf5nLC+HwjpCgQGrniCAaEgV2nMiWM2ClrLmib2mQKGa5JHkC0G69Jw555xSoH1qO7rHNyBc9PDoGiCgaEnutX2noVSxVHCtYuM2Sl4rVJWPoe4ePs5YHBpJ4OLnP4u4UkHTx34CRNvmu0uvWbz57F48eMdV6G+L4ra7X8JXH93vVFojBLjmL1jdub0PAPd+yKqD4sOHj9MKlqfFWUOMI8AtVqNmlV6tYHC6YOYJUaICVJBs7j0XiPdJbYhCEE25457Gb6jMwtMUvYqjkzlsPSErBepSbSyrz4RLeDs8aED/0G9Ym5JxyeWmWU8yxYpDtv3weArJfNnsk9Wme5jZsckckimnaAU7D/unM7FZqhXGDcFndh42v7OHiQrddG1TJJAapU41TY9G9oymMZFlxEe8/gNuERJgxMXSgxDaErrbfOjX6B96GO1T29A9vhEA0JKxBCeaM4fNz5pODalvanp5FK2EhcOPWcOjFET0oCkhdozRXrCSAQrTOPj0j7B3BzOeFb2KWO6Ew+iWpsLlDqxoOtLFimn4U0rNMDgRkeKY6xzrEglwQcHy0nhylmIKOPS442senksIgOFtjMQVZW+1aFwPTOVNb669P5aiIFd1pHJhcwFUIG+UwtNb2pbcZZ3faP/EVN6hAm0ft2aqCfJBsOc3ZyxSTGRKJmGO5QbN+5RAd6RbUFCEywlpjPxYXjJIoRXP51eEw1OZOCx95KGqnbEAsqUqsqUqE8oR5kefsNQUvTmqtMIjnF/0/CuwX5h0sYJYfhChctIkmd6giGdl4RBCdYmEuvXPL1Tt46Sg6xTHv387LlAOo3T9N1ltLh+nFEs6Y/jF7Vfgg5cswtefOISPf/dFaQXIxOv/EHjPt1jtlns/BJTdf/R9+PAx/xB/jO1FdE0UprFnYAyP7ZIVGSlR0TX5AtqSRq20juVmaRMvUUAvgyVYySBQyZhej+ls0VPVTSJoVGMGYrjF1p6QQyU0ZJEaiuFkAfvHMpjMlSAaQicmMzg04ZJjY8r7y4b+wK7nEC2MOPaH0GqoPO069u6JjaanydXj4PLVjqEkMsWKc2PyhGsbBNTdM4DhxB3FAAAgAElEQVTGBAGYsevcz+3IWH7IQWyDlRRaU/vMz6lCBQfGMghUswiXmGHNaj/ZPLiEMAIO5t3tPf6AXLfq0OPI561FwEA1h/Zpp4erNqglQS7kyHGPW0MtGHMYLsmFrXXDO7j75WcwnMwb56gBN6+F2/WxFZoP0rLrrm5qfEGFWHlcwnNhXxyoqmHzbx1Uqt9mh1hHEQDGMkWMpuWx2ImxfYGX2v41BgAAUPUSAlU2f8FKxnGP6zpADY87D4VWjMJ8eaGmKw8jdPSfsGs+nCw48kvzR19CqiDm4PJ/NewbTbM6bUNJ7B3JmAIhtJS33hWuZ4TtYgkETbfNFSfVxrXaNeixEARhQY2Py57nBvl5L1Q0gew6IwjqwSdoPlzx0s+/ijcXfos9qz6J1ovfP9/dOWMQCar45w+cj6+87zxsOjKFd3/9WTMZWsJFNwO/923g2HPAjz8CVOq7y3348PEKwmXp3K6OKP7c53fcj05RudHYQzZKiSnu4UbQWtIHXD0YHL1jlsAAAZVVHKnTaLH6T1n5D0HoQ5TVtmdX8X+HDSlyTZfblAxbl9AuKrQCStGUO+HYx362WghUc2hL7vI4XuyX9ffQdAGdic3yzmIpAjDxlsksI5+a5R6ynaABY4xYM+KVzlcLwYpcU4rLtIueLmmhQAhx5GcOaDnPPCyAGdh2Yjhb1NGx8QQPreTgpKFQ0cxrx8lFk1Hrqiamj1k5SwCShRISuZKjMDzP3wuO70CbLW/ODkKIabhzL1mgkpPKIrC+C9ABWmNSFK327zulFFM5QfAjewxacshGxhSUqjqOGDmVBPKtapfJl7pHrTpeXEzF9JrXKR8BsAX/qVwZw6mCpH4JMG+zKIjCfbjENh9ptd30BlPdWjypV1YEgLSoIJfVIPAOyXbCLg6jai4L6NCli3tkUgw/Nsbmy+z7mC0Se5/Fxbv+EdvC63H2Tf80390540AIwU2XLcF9f3g5CCG48c7ncc8Lx53Jted/EHjPN4EjTwI/vcXPSfPh4zSEtaJKPI0Ju/FmwmbcH5jIIVPiCogehzRsb+hGfhvDaIoZEpliBYeF79undgCUmkWDOcRaRnxhORKw8trElWSVABjbZUpgu608y4OAEN4n0TUHtg2Jxp37frEaBG8mZEHXNVMVklJg72ja7GKVK5zY+kBQX4FRIURkpELfZslkXCDOOQ9xZN8bHhHQmvdO1XWiXLx+lP1P0cromtgE1cVr5SVp7wW+ezHSxQRAOAHiwiBEVAjlBO246zkPj6VQ2fZTHN+/DZs3PCoZ7/uHkzg6mTPb56hW2G9rIHnIQRLt0CiV5lqpFtA79pTcF6JIniQdwIkp93QFAssjR0Ch29RX+TlLQgmPtuRuTO97ShIPokTBpE1+X7wMiu5GNnj/qOmJtfJOqaMNL0zmyqanTfPIz9UpxUAiL5TxcPFOmXlnVth3Ku8eVikSL3GhQvbgNcAuBXQ2h6TPbnNGqC49K9x73EsTZl6k6O2uBZ+g+ZCRGYV6360YQSc6bvk+iC8KMm84f1EbHrzjDbh8ZSe++Ktd+Otf7XKKD1x0M/DurzE1oJ/d5lITyYcPH/ML9syWwu2guj23g4U+7Rt1l1u2r7TuHc3gheNJc6vr2Ro0fu2hd/tHM6jqOvaPZZArWe+RSGkCBMC2wRR04f0iGifcHmmJBqQQR9j+4mFt0rld+itTstrjSbWdXX9Ph8CJBT5fnZObJdELt7b2DieRMMLO7WQwmDxiKGXaPWjyR0cBbjCCa9p00tx4dnvmEMh+IluGvv+3hkeQEzXqSXCB+uUbzNMY/2/KDSBcmnTk6MykLY6iQD76Rp9Ex9Q2NGWPm4sEWiBqntmdSFoezz2DkzieyGHs8Da5T9Qiq+MpmSwRAG3Tuxq6HpRaixdKdgSk6hQmoVCh67rpwaaUIl1wJ0iKIh/pJkDkNZ05aeGHoCLuSBp/V+i6KL9vC39ssI0iV8v02H5sMoetA1a0gPNdaS1wiaHiYx7COyahtEFU2DX8iNJ2+3tRN9Qtm8MBZ3kFN1JLqWvJBqIQ0+Orat5196T26+7h48xBtYzpuz+MUDWLFy77DyxZ1D/fPTrj0d4Uwnc/fik+ffVK3LtpAB//7ovOFaP1twHv/Bdg/0PAzz/hS/D78HFagABUQ7DCPDwUqiOMqVDRcHAs43YwAKv4qtimWafqpD1odsNEFww9eyMU5aosfS8TNMPIlwwe9m8mvtLskxVmJ+S42c5VCcZRaV06O24iHFQOtVtfN0DQRLEVL0znLA+EpDUAHRjZiq7JFx0CAHaS7SZU4uiT4RHSYp11920UolfnxHQeI8kslMNPWCRHMHp74hEAsqfLIVoFQ8LdUW+KXWczzM8mRQ94G+lAbYO/LbkbbdEQooVRtCV3mUY4sYnQuIFSFoZKKEVVp5IHmG23rtW+QVm9j4DaPHLOc7VEeCkBppQKsDlz9RgRBdVq1SRf+8cynsIRYnkGQnVoZWekjBfhjWaOSITD8vIao2jwIXMLA+ZkpXEvL9/ffSvznOnmfm6hh2YYq85KW9TrtRsyAml1L+tgmyPh3WF/5youIY5e4YsKIdJC0WEXVVrHMXX38HHGoPjgn6E9sRVfb/4c3veOt813d3wYUBSCv3jnWfiXD5yPF49O4fe+tYGFYYh43aeAt/0jsOdXwAOf84tZ+/BxGqBv5EnE8iwXhiqqpJTIYQ8dFOFcoSWSlcBrFwFAi1GXyC4e4AWneAXF8QR7r0QLNrLCV67FnJVqEX0tzJAfSbFzEmKRMK5MrqkR08DjRrtkjDr6QWSjqK4BKFhNwq6F6ALraxeSwL/nzdtXx12vi9Bvb8O0dn/tRjLA5LjNOWK+AuN0s3ehUZt5F9BkT06uxIqnW+Ff1rkyhgdAvJfcPH8ATHEJfj4KJtgSKk+jsymEuO70Ds/UgyYiGnKarYFqFsGqU3RGBBeeUbWCqygLhRU2x59ZDnt5gFDZmRceDRrRRgQIltmYh1MF7Bxy7styn3SZ9HrlKtpIQUW4DoVILwBvr2FkYpcp+hLLDzo8pLU8piKmcyKZNe5To1+NmhpmDXjhudk9LAgNgUAR34/2gtnEWvw5OJww67udFAwVR3uZCxGmCqrRSxHuIY7u73NCZLKXLJRr1uezzunDx5YfILLtu/iO9m6895Y7EFD9W+N0wwfXL8YPP/F6TOfLeO83N2DjYVuNjiv+CLj6z1mdtEe/OJOldB8+fMwhiGFmq7rgcYECpZw2a1E1gubMUVvDFnmhlJEfjmhIDkdPtdZT3rWH4lGz/lqkaK/FSEGJvDYcKU0gHGB9MT1oQl0tKUjR9KA5CZp9xZmvalsGk/t7LB9bhEqg2XNEmqCS5wVCNaiDmwBKoTaQjiL2VdMpxnqvcZyZ1Hntai4ELajaSxgY+9iN1BnA7jW0q2Dmy7a2hWvCSaQot3484VEiwDBSqZEbdXQyh67JFxEuJdDfHkNr1JkmkSx4PwM6pZ7k96y+FpfSwo2BgpGJptwJSXWU49hkHp7kWlAX9QLzhrHeicIjbp4xSlSHIe8pVmE7qaiayGvcTeXc88/dvJ4c5apuLqzUQ068V/izjJl50KxwTus7cRGEEKB9Wihs72B+Vp5mpVRPudq6vrX7xwNyqef7hueNVXSnv011IWicOJbCXdL3CiGOZ3L3sHtou3lMza0+zgwMvgztwT/Bs9q5qFz7Nzirr6X+MT7mBZct78D9n3kDuuNhfOx/XsSPX7QlLF/zl8DrPg288E3gmX+Zn0768HGGg4I6DK5gJc2KoM5AplxxrSvEf7ap5E2LODwLbFvIY7GtXiieyxHYMSh7A+ykkFLLQLEUqV3EUWwy/vJpiOHtMHd27c10xwUY77saojGmta8w/y6FO5GOr67ZBgAo6SHmVVHc56ktGjLDJSWhDQroCi+qK7Zfex7d5PhFgsbOQRFUFFPS3BUz8Sy6wG67L2q1yD4/VBSZ8ArNjBbG0D/4kEHMCeRwOMyYUBXKGrYMMLXIdMsaaVtAIZ6hvfVAweY+WEm59qm2N4ltOzHtTQyYAd5Y59xC67xCHKu2r8UcKm7wj2fcCVotcuIpTFQHZr00F49YzeO4x81jf51SaWFIO4lUjXzMSs+p6a2l1Hx2+bTaPfbcM1yoaIgE7Qsp3tEPdq+9QohHSKU3fIJ2piM7Du3HN2NUb8ed3X+NT129pv4xPuYVvF7aFau68Be/2IkvP7jHWikjBHj7V4ALPgI8+Y/Apv+a38768HHGwmYYEAWZUhWhUuNS5fYwNQCocq+Z0Hx7LISg4m48uHkLXPtXw47xIm9NIdkI6WiyVM64LUMJkRbDw8VJk7xGg+6hh4Bl+NXzSIlGDw1YJIMSgnKYEytvokMpRfv0Tige09QeC2LZ+VcCkHMCdUE2W1SJi2csUQyxbtJo37UYXvg2V4NW5NBcyj6gEgxM1grbq0Oo65AFu6EsXDqEW7oBQBaV8IBoVItqioAxO0I3dEVWwVvcHnO0d0Soj8dD+KQ2XYalel08EZSFAgYrGXhw8RrH1p8HhRAQ6jTBXe8915xI9+vpII5CX7xCdzncwmnnCvw61DqFmAdat5A45PujWpUJmqaGZiSJb7YpHJJsO8dzPz7PLen98gbhWtkXpIhX4XrAQdYJ6l8vO3yCdiZDq4D+7FZouSncXvlT/N2HrvJDG18laIkEcdet6/HxK5bhv587ik99f7O1IqYowA3/AZz1buDhPwO2/3h+O+vDx5kIlxwvoPaqKwc3JAh0B0mrhlqAYEwyVQhx5lDx83jZri3pA1IIZU3jh8pEKNe0hB0Tkg1s8ffDIidEypvpmtxkGq1BVUGnwAyiQRWE6jg0PGnm1Sh64+VDZPJDYAoO1CJogKTe6LYdBvEQw1OpQNDE+mCBikUwAoqCdQtaABBogRioEnQVSXAjGIWKhkrFW/q8vlR346v16/paJCK/cvkKxz7hgLtxKRrVuj2slMj331TXemlzwCWuVPJFqiFMtV9oPQ8eQ+qNR9w3CKjqOlKGhPtUznte3RBsIP6VkT7rnuBwy5VyM9S9ci3726LS55Qkna9isusy1+MIiKR+OdcQFSgbQcrIa9Q93jO6EkI10GR+rmqs70P978J0+3lIta5DfWEQDms/TXr2BW+7Gm2I8IlhifbHtFbUgcODpsCDmHvDt8bPZDz6RZDjG/GF0ifwrre9Dat74/PdIx8zQEBV8Hc3nIMvveccPHVgAh/4z404MWWEYKgB4P3/Ayx/I/Cr24F9v5nfzvrwcYaA535FPVQBlQbyinLNyyxi5maVRlpNSQmA/ZArNuvBqQDpRGtqj/CpcY+MaXyotrpAQhesaCCCTKFiGnLVQLN5LoXIHj6Wk0KRblltCiFxEQoRic5LXLsoedOIYhlXrnlACoqRXlSjXQ7Pjh3EDGW0DF6dAtTt0pQmrOMIEAoo0mq6m0loJ9ccag1y2l6oXY9rJr6GmE1CPBhw5o2VGjD27TW67CGOoWAA0+3nWecRXFmciHBinmtaAl2NoNDUj1zTUqM9i3SL4LmQmhJ2ePE4jk7mJAU/uZ/u8z/RfQUAYE1vs+t2EV7XsBb556BQoGgltESCQlguQ1BVsEAIPxW9mpQEJKEgEd3x2vf0yYKPtpaTNd2y2vSi8Sgfr6hdnQSk55QpdDJRpHzTEjPfriGIXkZRj0ggSDpRwZ6S2k+KuECmzii+1vY+nkVsrk/QzlRs/zGw6U58T38XEituwCevcq6Y+Xh14JbLl+F7t12G4WQB7/3mBmw+ZtQSCUaAD98LLLwQ+NnHgaPPzGs/ffh4rSOgKCiFPaTRZyraY/ygU6JiquMiZJuXm5u4yEI51Gbu61jdNchELZVIgIXpLC0fwsJQyTWkEuDeNTcDQ/5ONGC4B40a9Zd4DlMh2mcVR1ac/QalqAbjSLada4zDaVSb44a8ik2lmlOWMR8rDDva0JUQEl3rke+/EpVg3DMUlIICBkFTbAStnpeK90CcV9cQR5dz6x6GNwAEFYK2qLNgMUcx3G0KGIheiXp9FT/VCxvkpFYkrZqN6BIi54xdtrIXxUiP+TkUsObFniuZFIgcb8TtEvXGI2g3vLDFaA+qQXcyVVMt1WOofO5CDcREzsYAB4Dp9vNAoCOg5RGPBBwLOLVaLYdanV5LA3bhGY41M1yIdwtDBayFFbe6bABbiClFujHRc4X0vVeuH1VUF49W7XcmJ6f2Z0Vspyo8b7GwdX9SokKtFlwVOeXG2Dyu6GquES7uhN2DZj+Wk/9a8AnamYjhbaAPfA47AufhG+ot+OqNFzpWX328uvCG1V345WeuREs0iI98ZxPue9mQCQ7HgZvvAzpWAD+6CRh6eX476sPHaxjMKHJ/l870DWvJlhMUYguRaltnbpvKlUEpIyojC94CAqeBmG1eJvTJG30jT+CCyDj6qkOoBr2MeVo3wb0SaAbpWG4qS5pRYWauCjOU4plDZs5WSFUk70U0qDrOwiXLZYhjElbLq6KoSm3RBj6/OmWr954/gRQgpmdIlC5pIC9JIcwwE1fuXQgaE5iwhUTZvGei8AHgnlvY2xKB0rMOia71UAgzxhtRswQhcvRVIIxAHVIy0X05ACCmWXX83MgCvy9DqoLmpmbwG6KjKSTfsw08IAGXi9TW0iwdSqiO5nDAlWB65QC53Sap1rMED2kjOWh1d3GFTiyiTQiBqsnKim5hoJnmFUh0XopSpBu6GsbIgrc0dH8ALD3Ci8S6wS6MYbVv9N9Tnr6xCZnsugzT7ecxMkz1msfZFxv49Sx6LYpBXhBpiggLCIqKgFZPDdIah9itaqBJWiTiED3CdsVGAnlO9Aby0XyCdqYhOwH85KNIK624LXs7vvLBS9DbUj9+28fpj5Xdzfjl7Vfg0uXt+MLPtuMrD+9lYQWxDuCWXwJNXcA97wfG6+Uu+PDhYzYgxF2hjcHdkKkGmtwNJi6n7/JDrio8OIdAVwIghDgW2SqhVky1X4hFthwWO0ylSFIniZ0QjPe8AZNdl1ljJFaBXv4Fz6UhproH23cq68z7CaqKZPgsao+aMUmBKgtxjGePOI4TDR0xv0wT5564h8NxlCJMCINSprjpZWAzR5loeIlzZJGPcrDVcSyx/aUYCpV2KIpFqJ1tsGPzsUVSn9y6u7g9hngsAhAFXc1htESCaMjMCzVLBZERbUc8UjukjF+DlT2WR8YeKkpgIz9q0DxuYWt0xqsWhDiDEakSFMgI81d2NoVw0eJ22CGKVtjbFVEJNCMbXwmzg3NUsqYnHnZ6sMSafy7HuBJloqAYtTyRuhp2zL0nYexei3Gb9yYdX401l74V65YtdOweDqioqjGpriDvqz0cM92yFoVon2M0tUKIK8E48k1LwO702vM80X05ptvPNz97hT2mW9YiE18JwFYjTrGe3faYtZggihvZQV0qoJXCXaAkgOWdFmE8q68F565cbB1HFCztsLyPVi09472u+ATNh4hqCfjJR6FlJ3Bz5g5cd/n5eMs6p0qSj1cv2mIh3H3bZbj5dUvwX08fwe/f/RKmc2WgZQFwy68ANQz84L3A9LH57qoPH69NeKwAN/Wvc/0eIGiPORfJzHpnLonlqqKgbOYEMdOaexcCYvgbaSz0ihm+zjo9dlRCrYzYmPsRrO6Jo6s5zBuCnYhyMifWbwKAcrAVkaBF0HQlhGgwYK5M24U9Uq1nAwDW9sZd+1kJtjhSzexkOd+8DKN9b8JY7zVIGh5JnTIlQq95ohQgikX25Dw39reqEFAlaOZKcRDCKQMDJ2ipgkxWQwEF6Za1ZlinCMWcH9kY9XJwEbNPxmdFwWjfNc5xQbHytYIx0yMYCaiAGsSSDvfQNqEHwv95H71DHGXxfWfO5GwVB2UjnUDRK57ETyeqazipeO2LkV6jfAOkHMZaiqOA5T3pavMOIeyOc9JsF7MRYLuJXT1YLjmVYugoYI3JEeLaey6oEsTQouvMr7LxFSCtixCjRUc+XijAyOBU58XS94TAVEkVOiaMxxrjeM+VSHReAgoFmfgq10UOSpS6RFhXw9I4+TNhJ3bVYBPSrWch27xcktmnatjyWHo87/GwjfS57EeoBgqCaEg1xXNURQ5VpkRFtyFe0xwOoCkcYGPlzwMJ1FSVBHyCduaAUuChPwVOvIA/1z4NuuBC/NW7zp7vXvk4BQiqCr783nPx5feei+cPJ3Dd15/F1oFpoGM586RVCsD33wtkRue7qz58vAbBfoHt9SRjfasx3nOl6xFu4XKmcehCRo5O5tjKMCGmAaEQgjW9cZzb34q+VsFr1qCXwmjFc7sYepWJL2cenc6VIIRgWWcTLl/RBRCCWEhBLHcCzWObjYat/nF0NIWwsqcVrVErzK17wTKoiy5G2hBZsatdcsMsHFSlfsbDzEAqhTuhu9RU4wipCvKd50ALRFkoJ7GKbKdaz0ZLjZwuTs0Au8iLNTZdCSATXy4dV+Gkw5wDIN91AQ6OW0qPkYCKaDCAt6zrg64EoRA5v8yUMxeKkms6TFIctBEdbpCqBmEgRIEWaHKISbD7yzg2EIZqzEdLNAgoASihGFb3NKO/LYpmw2gV1RLN+1MR23QhP8Y5ci0rpeMU+VDXospvP6cP77mwH9es6cHqnvpheboSgKKVPUU/qBJwJeLiFPL+9cQjEMnGOQudHlKpDYVg/dIO9Me9iZybEiYlxFx8IA6Xo3UdpXNRDSu65PkoRbrQsoIpOjaHA2YzoiiLdRJnH8R5Ee81dm+z5/TiJaJsvtNDTahuksdgxQp91QIxFKN9GF70TqRb12Ks943iUUKLuqNNDj5eSXCHLzB4qLQSquP4lBXGSAMRjPdeJUcBABJfXtMbN0VZ+loiDu9aIdrHhKAIQcQlJNsin2zLuQtbsbqnGbFQAAtbo5YHjRDkPLzmHD5BO1Ow6U5g6z24N/whPEauxJ0fvQSROitCPl69IITgo69fivv+8HIoCsGN//U87nruKPTus4GP/hzIjgM/eB+Qn5rvrvrw8RoD+2GO2WqEqYTg3MWdjhVaClkJLd2y1vieryy7SHLbPnMbriUSREBREAupaIuFcNnyroajyAhxz4vgBEAq0qyEMN1xAWBT7QNRQEDRPr0DapkbaOz4pOA1UglBr0Eiuccn37kOpHMltIDxvU0sgRtmCu+sgSbBw+As7My2BVUFi9tjriRMpxSVYBzxSEAyQDlKPefVILlsQ1dzCLoSdFyrqUC3FD6nKAR2qQou4d4UDuBt5y3GxUvapVzGRO8bMLLgzdAFo7knHkY4oGL90g5csLgd/W1RNBk1mrgogulB4+e3G+ZEAYiCvhYWEhkKKFi3sIWFmSoBYPXb0drWhQUC2Rfv6dev7MHK7ub695exQzHMPR+KORd8W6r1LPS0WASyvy2Ky1d0mjZKayyI1mjIdRj8OSEg0JUgCrGFUp9EgkKJap6nFO7ERPflmOq4CJmuC4R9FCzpiOHylZ1W56vuapp2ksTBy1CIOL+/zUEOF7ZGQYli5gkS4f92iN5Joldw3qJWrO6J4/xFVi4UNVRVCSxvTjncyeY3Hsb5/c68KaNFs28sTJtdo3MNUrpmQQeuXtst9Z8QJlUvgeo1S1pwaIGYQFSMQ4niWWoAAMLmcy6EThoEjb8zWDviMyj3haphaIGoGd68uqcZi9pjUh4djybgY7R79ZJt5xm5lmzOTA8xBQCKya7LkGo9y7ymkaBqkWxCkOi6DKR9GWgd5VjAJ2hnBg49DvrIX2F781X4Yvp6fP2mi7C4bviCj9cCzl/UhofuuApXr+nGPzy4Bx+760UMN58D3HQvkDgI3HsjUKpVDNWHDx+zgWjMLGiNYElHDEu6WrG822nU8XCyya7XIdOyin1ZI8TRDrvHQCEEV6/pRls0WK9esdUGsc4JWEWkKVidrEx8Ve0Gll4OEAWKYdDYQ9q8zsW36kpY6isvV2CBGznyt3ydkRLFrHNlxwWL2tDeFML6pZ24eEk7LlzchgsXM2OVUsM4BHH1roR717rOLx/I2t44QgEFmhp1XKtyqIOPGE0h5r3RqexJkcw/HrJFBOKhqBI5u3BxGxZ1y4b2gtYozl7APLbcg1ZZwrwU1Ui7cR6rb0GFgIIgHFSxqD1msp5Y0PAwKSor1RKQjcjy0qvMv7tbomiPhaS5IZRi+aXvlOfKXGiQiaIi5JPlY4sRUBSs7mnG6p5mLGiNoscjN76rOYzeeASxUACFSC+0JmZsX7K0HX0tEUy3n4/8qncDioo1PXEsWrTMPJYSFQtaoyiH2jDZ/XqUwx0oxBYCsS7hDMRaMDGtb3cFyI4moUD8ggvN75N2rxVr1oLxjCxsi4IF6An3NtVdn3mpHpexeLFuYQu64xaxjQsiGOKtnI2vRDigSqqZItpiYTOUUnw2OUFe1L/ICM0UhkOIo8xENRhHrdpg7rA8aLVqHpqqsMI8hEJsvNVAE0b7rkF66TswsuBN5vZipE9qgwjeyFBhHK3REFugsPfI6BIjVraQbSL60wUfq/FFOdyBbHyluyIuISiH2xFfdbnnOEX4BO21jslDwH23YbppJW6avA1/8pazcPWa7vnulY9XEK2xIL7zsfX4x987F1sGpvH2rz2DXyRXgX7gLmBoC/CTj3quEPrw4WNmILTqqNPV3xZjHgM1jJCqoDceQWczMwwWtEbRHHWq3/GVYLcfevs6s2mMNXV5bJBRjPSARJ2r6ZSoZnJ9VPCWqKpTZVBCfAFTjDXDlKw+UkLQ6vBcEdMIVAgw1ns1dEolb5Mm5M70t1nkRyRR7z5/IZZ3Rs1wq0RWVsCzG7qhoIrFHTEs7WwyjU8WWudtCrmJaInFtXmfS+EOdMXlhU9uzJ21oBVvWN2FoEpQ0ai0Yi/lUAm5fdzy62llbV6+ohPn97choCggvbbclViH+ScXRVDjPY05X5gAACAASURBVMCad2DZ2osAsKLPHO1NIYAoKFZ5CKYiCSgIHZI/NfV4bjNGg2BrHzqbQmgTPF7pljWoOPKVAGKMnRv6rdGQ6SnzgkIIFnfEEFCMwtfiNaYaO6EaBIiKlmgQq6TQSHcPjSKMnRLFWQph6qj0UZJ1J8B0+wWgAskTvVr1QA1PJmuK4Ozli+Vu8mtNqekNdBOUaQoFEDSIP4FL4Xrh44WL27BUELi4em0Pu4/VEOOI4s6dK6X7i4N5aBVMdL8emfgqjPVchXzTIvTEG1ANBcy8Mf6M8npxodK06/5BVUF7LITz+q376JxFHSyck+rQAk2Ix5tx/UXLzO3FaI+Ua+d8DzH098laDL0tESxojaAnHoZi8wgubGPPI39ul3U2oSUSlN6XxgCFv9kYuZe7ngAPh0/QXsvIjgP3vA9lquKGxB/hDeuW4jPX1lkF9fGaBCEEN79uKR7+3FVY2xvHn/50O259vheTb/4qcORJ4Od/AGiV+g358OHDG2oQlWAcQeIRqmOs4C7uiKHzbCZEEI+GgEWXohjpRSVo5a3x8B231XRHiCM3qJZf3VA3dSWEQoSpsolFgClRkG5ZjVLYMsgIuICIiwFvGnJWrlWPkackhtDbjbZoyCIEhBBUAzFThp9DVOHrbg6DEoJyqF0au6oQhFQFy7uapBApTpC1QNQMGXV03fi3qlOWg2Os0K8SPJyZVTfIwwQzvsVQSXMGiAooqkPtDmDEIxJUEQsFUKzooJSaoaMTfVdb102aA7Z9aVcz3n5OH3paIpYHxK5eJ8jb62aIIwHCzVjU0YSr13RLpKJU1UGJKuc5Bg1yucAK9+MD5wIeklCGEBJngfn9ll/yNqxatRZQVBACZJuXu+o/kAbqi3lhURsLWW0RFjfCfczrGgup5v0VVBWTLHoVbw8EZIJWq/gyAIz2WTlUVAki37RIIjXLuxqrPQcArbGweR0IgPBCm1BM1HoW801LMLToOjNEjx8DsBBZInrZbARNi1sy/Es7m0wPsoR29i6QnnXVnTAHVVaAvRzuRLp1LaqhFqM/MxV7Yf3kqq1eHrhIUMUb13RjhaAaSloXYVV3M3oWsJBSSgG38gLT7edhzQVvwErx2e62RE+iiy/ExUvazRBnhRC2qEaII8Rx/TIm6c/z32LhANb0xh3zTYXyCQiyEMyeeBjXrO2RwoZrwSdor1WUssAPPwg9O46P5j+Pjv5V+NqH/XpnZzqWdjbhJ//f5fjf16/DluPTuOK3vXh6xReAvQ8AP73V96T58HEyCDXjuvP7cfXZTrlqE/EFQM/ZaGlmRlJncwQIx5HoWi95OXQ1hHV9LaBExXn9tQUKCAEQaXXxmFn5FHaUm/pQCncg27TEONYwzIiKTHy1WT+ttzVibJPbuXJVFxAyDJ5mYwWaKOhoCmH90g4zt0rsg66Esa6vBd3NEcNrE0BbNIj2pogpP94eC6EtFsKSzhgSnet5E+hsjqHrvLeCrLtBHgjVhWGbeonmZpH02qYGAPOgUShMKCLUjLZYyBTDyJepuCsiARUhVZFEJSyCxgy2qc6LMdV+IVKtZ+OSpbLnIRxQUNY0aLol/qCpUaDZMLijzECs6roU4ujIF7cTNMEDVDUKB4s1w9piIaRbVpne2OZwAJoawroOTtBUoNNYvG215PxN49m4lpGQYDKaBE0OcVQIAVoWspDXs9+DytrrPeXQictfjSIWDuDatT0I9lgEfGVvG65e043O5jAbEwDoGnqNvDN+D1cD7L7lngyRKHY1R3HOQo97xgBVQuZcNhk5pYraeE7/uQtbTNGTy5YLuW6YOWltCgdwydJ2XLK0XQgjhUNbqNR3KXDO70nfiaUbZBCPvxkoUQxC4hK+bHic0i1rPPv85rN7saaXkyXWhiXPz3BWXwvOFoSWXKXwm7oQuPBGdHUzz65bEXiAEduWxbKKbiUqRJIFIlCIe4hzxPB6BVTBuw2gwkujtCxkAmwGOPEtCiTafF6p5unFc4NP0F6L0CrAz24FHd2Jz9M/wVDTOvz3resRCzXmVvXx2oaqENx25XI8/vmr8daze3Hrnovx1eAngf0Pgd77IaCcm+8u+vDxqkVAVaC2LgSWXI5ipJf9IC+8yNph2ZUsbIlSVuPII8dMV8OIhQO4dFknVnQ3S4aw3QwprroOWPkmuMLF9qVEASItmOy+nK18m6FNCqJBFcu7W9DfFsUFi9rQ1xIxtjEDNBwQcsciLcBZ7wa6VnueTFcCqJ7zfjPUKMZFUogCrHozAosvwRvXdJtKgW9c022G4RejvWarV67uwZoFbUAgjFgogAt4GJlplBHTyKsIdeVML1FYNro5aSxXdZY7xxQB2PEGyanaREcIAbDwIofwByB7HQpN/cjGV5ghZ2Lela7poKAm6ZEUPA3jvFy11OyI2/2h2ow8IQxrTW8cLdEg4racoUqoDcP9b0N/WxR9LRFcsmaZ5QkkCgtlO+d95mq/2O8V3c1Y2dXsqkIYUhUsauceIyqvESgKlIDsPXUrIH1SEMgpIQRtMcOQbzNqUqkhs9+aEgGWXYXp9nPN/QFGggGgIxbCuQvjJulyA/dsj/e+AQCwojOGK1d1IRKqL/rA0RKxRE+CqujJZFe9EBMWeHgfAckDJGJRe4x5V0UPmu1ZpDy3UMB0+/kYXvh264u2paAA8rEaC0ywwq7feo7TW8yfof6Fiz3TaZrDAbQsvxTtTRFTip6HVgPsObGk6Rnc7hv+ldciFMe6BW6EWzhG9BIGZe/Wsm5GppvN9xY7Lte0FFj8OmDJ5UCn8f6j1AodJQToWCGfcoZRSj5Be61B14D7PwMc+h2+FvlD/K56Ie76+KVm2IkPHxy9LRF88+aL8YM/uAyPNt2Az5c/Df3I08j89w1AwT0O3IcPHw2itR9vWH8RVvfELQ+TCG5Uuxjgbz+nD1ecwzwa0WoSgOwRsYMEwpbx1boYWGrJ+btmChFVXi0OhI2kfxVBVcHaxb1QCDG9aETop2OVOSj8trjWJ4ubhpQkAqCoLG+tc6XjGMf4CJG8g29d14tlPIysbTEoZSvw+abFGOp/J7SAlQtmESf31fVErgTYBUIIpJIIUtiUGpTqHQUUNk+6oqI9ZjPSTY+GJcCgGWF2AYVgqv1COIQnIV9r1/psdo+U4Dloi4Vw7doeDyKkYEFrFIQQRBZfZBE9UzLffv1YGyFVYXlrYOIt3APF0bdgEYKqgkqwxUVQxWjJGMdb1/VaHuH+i6EpYeZ9FBcx3HD29fLnUJ0wwp51wNk3AMGI6c0txPqBeK/pXeNF1gP82SGAeJ+EbaIaFy5qw0WLWd+5Sp+qEFbywOXebwkHTKVDORJUl/42ax5Sdr2n288XVBstD3Rdcit6M/svxljvNXX3l7yb0TaMLH43KsE4Ovi9LN5/q96CqY4LzfFEAipet7zT3NwWC5nqhE1BaijJduDqNd1457k2Mte1Ciuv/RiuWMVy90xVRyhSjmYt8PdTTzyMZZ1NZu7fhYvbcM1aK19yhQuxlULH/3/2zjtOjuJo2E/v7kXdnU7hlHMOCAlJIARCIolowCYngzDhJThgGxuDs1/sz34xBmzAGIMBYTAZjMAgMCCiAAUklHM+3elyDhv6+2Nm92b3ZtOFDad6fr+9vd3p6amanp3p6qqudlnuYSODF/F2OF1t8yIHHWn5TStjECBSFiZ/hIFlPb14EJdKT8LngyXfg6+e46ncq/hrzTwev2YWEweFXzhREE4YX8Qb3+3PS6tH89M38/hN6b0U37sA76UvMHyM/fwNQRBioHCEYTDZPsSD18iykp3hhIIBcBBwG+v4ROqb+T0+AIyY0/a/UgHDS2kvo0eMZNfePWhlJCqpaTJHdB2utmTlCsjMNULdMnKhfGvQ+tPZGU6a3F57c8emkzppcB/70PrQFP0dJacPDRO+jmdvla0MbYsNhy6gbUnUEcjW13Ye3Zltc3QU0JQzmBzPIfB5gw7hGrsAV+UOFvQfSkFuBltL29Z/ynSZOpoGgEOpQAiYp+84mtRQsm06oyP69WJbyxR6NexBuWw8M6EetFjx65lVYMjUZxSUb4vcyQxh9qy5OJ0h5XsP49DgYTST3a4qf9v7L4EslxP8nrjCEZQMOdX4v99Y47XuRfsDWz1xY0+ObqApFchCqY68iAPe/QE9Z47ow77KRo4cVsiQwhxa3V6aMT0WljlfC6cMQvna5kK6nA6jDh9YgltNRYPbZLYZ3vp6y3SyWirwHXE0bHrF3MXye1WOQHis2+sLrIXmc2Tg8LWC04XToWjoNZy+zmg+lbYwPEdObzwZbR6bWFt4RN9c9jY52wZArHvmFNKUO5T8up2BQZNBvbNxOhRen+bYMX3ZsXU4lO3HZ85pjHW+lb9tjLmkvqDvQvE6s0HrgIHmcCimW+bUWROggP29M8hAc5qm0MCp7e9hvYdB1W7j/6IwYZvhfj/9xpnXYRbs+yJuA008aD0FreHNH8GXT/Fi3uX8qvpMHrxipjFPQBCi4HQoLp49nF/cfgevH/kgeS1lZD15Gg8+8yKH6pqjVyAISUIpdbNSapdSqlkptUopdUKU8gvMcs1KqZ1KqRtDtt+hlFqhlKpVSpUppZYopY4IV18MAtp/H+iEhJm74g+1yRvklwswMhqG0uqN/OD3OrOpHH0uhUVDzbqcTB5sGbhzONGYnSO/vCOODYSJWT1IgXTXdhaaM3jM15+Ywt4LFPucnWidS7tFjv2E86AFR5WEHCGkOqWguvAImnoNg97Dg8PH8gfCyOPo3Ssz6DydNW1wW1IPU4YWjzewnpzLPFcZocYOhseqNasPVX1n2F8/jgxj3mBHGL0AxoQmkwlzhm2O3Ts3oy3cy0/+4DZvQZiauzS0MbdvsMEWCxZdhvfN5bhx/clwGh5FjeLg4FOoG35SIFEGGDK3v3Y1g3vnMGWIaRD4w+P83sfs4OQbXlcujb2GB3sW/b/9oTMhu4DxQ41+mj8ZCxi/xbFFeeBwUXTsZYyYcgxjoiQf0RZPrTNE7owwKfZDmTqkgNOnDrH/zZqU9z/GuD+EDBS4HA5a84dTPGQhOive69Pvrbcar8b823Ehi5SXDjyBksEnxVyzXeKQdobYtAthwGQCV2xmnvFd/qB2u8aMw2GEf/uNd/GgHYb4fPDWT2DFo7yRfzE/Kj+b+y+dwcIpNmE1ghCB3EwX519wGRUzJ5P5zMUs2nIzP9q0mXEnXMT188e0m9cgCMlEKXUJcD9wM/Cx+f6mUmqK1nqvTfnRwH+AfwBXAvOAh5RSZVrrl8xiJwIPASswnta/Af5r1tl1K7tHCHE0hYWJZwU6ov4uxqDe2ewKKRo+hF2Z6xt5yct2BUamiwpygjst/vW3tDd4tNk2c6Mpvp2FFsYrFtpZtB4zFmw7WBb84XdHDiskL8vFwZomHEqxs7zB4h2LZMQFlxnWJ5d11uOj8Dkzqe0/A5wuskYfS9/MEkaM7Ne+MhPrYtPWjJX+Nmib02dvqCql0Frb2/cOJ4w5CTa+6i/cti2MoRQgL55ldmI0qjJyOHZMBsXVze0Smvht56AO/7hTwmYHjMjg6R3bDzhx4oCwhrxPa3zObHR2DNkXteaY0aaXzTUjuAM/9RsEztmoeUbo3BabOd39xkLJOuhtZB8c1r83G4F+eZmBpqwpOpo+Q1sgKx8H4eefBelhCe11mKGX5fVGWHGmjfftlMkD23mXlFI4XRnWL4K2zx3Tj31VTdDb4lk0PWh+YlmEORT/bzBooWuH0zY88aQpw8x5mh0nN9MJdtPtQzPTxoI/RNISrh00iOEfjBID7TDD64Z/fxu+epY3887nlrLz+MMFR3Lu9MiTPAUhEv1Gz4DvfkjLUxfz0KG7ue/DHZz42aV8+5QJXD5nRNhOhSAkmB8AT2it/25+/o5S6gzgJuAOm/I3AsVa6++YnzcppeYAtwEvAWitT7fuoJT6JlADHA8s6TLJo4TxAEaooYm/g2s1VvKyXJw+Y2i73QIohcvhYNrQQlwj++A4tJ8jhxXiMkf/BxZkU1rbDA6XsQ6Z9gaP9AcWTrbMbTG323ZfwoTe2aoYwwLcsdI7J4PzLOfBv3jvuAF5eJt7wW6I1OHq3ysL3G1lMl0OsF+bGADVZyRjLJ4WK9a5L207tN0vveai04W9CxngzuaIofYZAx0KvDpMAgRnhr3BWTQReke4HuIlVi+VUuRnZzBxUPv298/jGlBgqSun/ZpoMRFIRhM/kbLn2RqRfsYvhG3vtH22XuP9Q5YtsnqFA4abjRVQNNF4meRmuph91GxwZdNqtrfX1QsGxrkskimbX4vjx/XnQHUTK3dX2urfzhPqJyvPqMvrJtRIH1CQ3W4R8XnjiyitbcbpUGEzKUbDbjmRcPeIrhgonjK4AGyn2kcf0GmHM8PwtpmcPnVQsMfYr4cvwk3FBjHQ0hl3E7xwDWx9k+fyvskdFWdw94XTuWj28GRLJvQE8geRdf3b8Pr3uXXtM8zLLOaaJdfx2Me7uO20iZw7fYgs2yAkDaVUJjAL+GPIpreB49rvAcBcc7uVpcDVSqkMrbVdmq18jPibrs2c4++0m6Ovx4zuyxe7wjvoLBm0A8Tah+iV5TLm/eQUGiPp5iLVc0b3NeqobARteNCC+qgZOdB3DCp/EOw0DuaI1H8J4xXzd9J7WTMJR/P0dAHZGU5w5hv6DpwWttzcScOgeJwxJ2v7f9sXiOM2F9QR9pmXU5YRTqq1pqHXCDyuXMb2G8Vcu9TheQOhvhSHUoSZ6WfK5A/Fsnh9Omr4hGPQkUYoZe8w6dhz+0Y1tLMznCycMjB4DTULx4/r32lvCM5M8LZ2eHe/UWE7kGANJe0zusNGYtRpfkONdblUlHDlSGg0rZl9gPq2agtzGBppECcceYOgZl9sRbNc5BUFL10Qrr3tWDChiMbGBvqoAjYU17YZa7mdm6IzrE8O+6uabLe5ws3ny+xl3AdiSF4UjnbLYtgkCZkwMJ9DdZGXNRIDLV1pqIDnrkTvXc4jvW7i7sr53H/pDM4Rz5nQlWRkw9cfgiEzmPXWHXzR7wA/dX6PW59r4pEPd/LTsyfLPEchWfQHnEBpyPelwKlh9hkEhPbASzGehf0x0nKEcj+wBlhuV6FS6gbgBoARI0bEIrdBwRAYPCOwhk60yfTW0f0jhxWybXtpuyxz4TH37TPKSIKQXeCX3eg45vYj0+WgJbMvI3pbszKqQMexf145I/vlUlxtzEm1zbQWEn7W0Gs4vc3jnD51EC4sRlmveELtOoHDAePsLweHUm16DJkRtapo6bzb0Xs4eFoDnXoNoBQt2UXtE234GTUPtI+pVc2s2VcdnL0ztx80V7d9Hj3fSPhR/GV8cvnx6x7OenC6IndUwy3tEEKkJX7658U5l8yOSWd3aveIHjQr/ccHfjvdRdcMear4PEB2+Adb4kggA0YoZmFuZlztWpibSWEmcNDFqH69yOlVAGOP7/g8S5NZI/syy97RHR6lYNjsTh23HTYhjpMHFzDZbpUCC2KgpSOHNsEzl6DrSvht9g9YXH00D185k1NlzpnQHSgFc/4HNXgGOS9dxz21t3PdzO/wPzvmccWjn3PSxCLuOGtyYKFZQegpKKX+hDFPbZ7W2jY+RWv9CPAIwOzZs2PvFSnVLkRqwsB8GlvDhMFYsjv3zslgZL9c8odF68DYdK7sOpi5fck+8huchKstsUUI/oGYkhrDQLNVNKMtJLNu7DnUHmrEP2RoeLPMuiefa5PSvT2uOBftjZfTpg5s348dMNkYud/hCXwVZx+1DWcGDJgU+Gg9lu28PP/BlJOR/Xq1y0bH2JDECHkh4ZQROuUnTRpAfbMn7Pa0Jo6EM3b4M3pGNdA6EZYb7yWk45kD5d9HQ32vkQxo3hjw2naYDv72lFIdM7rNc98/L8uwTHL7Ri7fVUTLBmrD3LH94pzmYbZ+RowZLU3EQEs3tr4NL34LtzOb6/gla1rGs/jaWRw7JvxkZUHoEkbMgRs/Qi35HlM23scHwz/jhRk/5q7Pqzjjvg+55OjhfH/hBFlzT0gU5RgzhUJHpgYCJWH2KQlT3mPWF0ApdS9wKXCS1npnp6WNgcm2C6qa8oR8LsrLbktXHnYnfycrhs6eK5NYpvaP6JfLgeom+uTazANxOIx5S72HM6qogIN1bkb2y7UpF1vn5qRJRbibuy8U0raTNXAqAHNGNwcWk+462tqh6+uOTEF2BgWS5MkWXwzTQY0CXTBgEMUr5HI6GFKYw6hQ4zxGmnoNpXLIuOD1CTtCB9fu6vTxoPPevwgM65PT9rufdHZsyYpGnRA09zDuPk5mnhG9UBTfskVioKULPi8s+z18eDe1hZM4t+IWvPlDeWnRMe1SkApCt5FTCBc9AWuewbH0Di4pvoxz5v+Ie+pP48nP9vPvNcX8z/yxXD9/dMSwFkHoLFrrVqXUKmAh8IJl00LMhB82LAe+EfLdQmCldf6ZUup+4BIM42xz10ndcQJJQuIZi++GTtaA/OyghBztMBcUzgZOskuYYZUrCrmZLsjpWNa+zjKod9cPNFn7nV3qHeywiy8FGT3fTE6ROPxe4+yYBzziRykFR1wQU9mjR3XMe+S/vLrkcvAbLnEmtojEpEEFNLaG8eJaz20n5hNGY9ZIy7mN1aOV38noNIejQ2GTsg5aOlBXCovPgw//j40Dv8ac0h/Te9AYXr7peDHOhMSjFBx1BdzyBUw4jdwP7+Ln+2/kowuNyb73/ncrJ969jOdX7Iu4PpEgdAF/AhYppa5TSk02DashwMMASqnFSqnFlvIPA0OVUveZ5a8DFmFJNKKUehC4BrgcqFJKDTJfSb3ZtmVxjGenjqV37nbSzKDojgH9Ll0XrGiSEV4aGvKYjuQN6NpMlDEwtqgXs0b2YXjfKB32znrQzMWdu5suPYJ9ZHeHmDgon6NGhElkk2b3hEQgBlqqs3UpPDwPvX8lTxb9iLP2XMYZM8bw3A3HBlIJC0JSyB8El/zTeLU2MPi1y/ir+gOvXzqAIYU5/Pilrzj7zx/x4dayZEsq9FC01s8BtwI/w0jkMQ84S2u9xywywnz5y+8CzgLmm+V/CnzXsgYaGGup5QPvYiQN8b9u61ZlomCXxTH6Tn4PWhoPlAyYEgg7THeOGGqEt/kz3XUZOYUw6az4F2/2Z2dMVMKWFEUpxbA+uVHX2+uIgRZ1XlsX0tEU97bkDzYyzPYZ1XV1RqPANMw7mRykpyAxSKlKSz28/VNY9QQtfSfzHfUz/ru/Pz87ezLXzhsd/UYiCIli8jkwbiF8/jB8+EeO2HEGr8z+Fv89+ip+s6yMq/7xBSeM78+dZ02OOMdGEDqC1vohjIWl7badaPPdB8DMCPWl5M3V39GLqwvmD1NKNQ9aPAyckmwJuozsDGfk8NBE06t/0PpNQhQ6YKCNLcpj26G6dgtCdweBUM04UtyHJbcvTP5a5+uJh4IhUHvAyEwqiIGWkux4H16/Far2sGXst7h428k4M7JZ/K2jmDdeUpoLKUhGNsy7FWZcAe//FrXiURY6F3PyjG/yfNY3+P2nNZz154+4aNYwfnjaRAYWSCIRQYgHf1IJTzxhw4me6N/TSUnTXUgYHZg3OGVIAVOGJMbgGJCfzexRfRmc7s9XcUAAYqClFg3lsPSn8NWz+PqM5aGRf+aPG/oxZ3Rf7r/0qG6ZtCwIXUpeEZxzH8z9NnxyL87Vj3MZj3PBpPN4Rp/Gb7/cz5K1B/nWvFFcO28Mfe0WahUEoR3+OUtebxwGWqrNQRtyVOrIIgg9kKGF8aVyTy3SOBS7GxADLRXQGtY8A2//DFrq2D/t21y9/QR2lnj53inj+e4p47t2QrEgdDf9x8F5D8KCn8DyB8lc8zSLWl7i8sFH8IrjFP6wrIp/fLyby+eM4Ib5Y8SjJghR8C9Y7PHFYeCoFDPQIi16nML4B/QzunldNkGIRm6mi/55MrB5OCAGWrI5sNowzPZ8gnfYHB7K+w73rHAwsl8Wz90wnWNGJ2ixPkHoDgqHw5m/h5N/BuueJ3PFY1xSej8X57jYmHs0f/9sFqctn83Zs8dx4/yxjLBbM0kQhMD8kvjmoDmg3zgoHBG9rBCWguwMpg4pYFgfuT8JyWXhlE6mfE9lAklOxCEBYqAlj6o98O5vYP2L6Nz+bJj5G27cMJUDO1q45vhR/Pj0SeRkdsFET0FIBbLyYPa3jFfJetS655m67kXucy2nxZHDh18ewV9XTscz9lS+Mf9o5o7tJ4lwBMHC+AH5eH3aWMC2MY4dh8zoNpkOJ8YNyE+2CEKyyO0HjRXJluLwQZ79gBhoiaexEj7+E3z+N1BOKmd9l9tLTuKdT5uYNCiT5y+b2eFFCgUhLRh0hPE65Vew5xOyNrzMyVuWsrBuBex9lA2LR/JszjH0n3ku8xacTk62LCchCE6HYuoQST8tCAln9ALwhVlgWehCZA6aFTHQEkVDBSx/AL54BFobaJhyMX/2Xcxjy1vJyXTzq3OmcOWxI3E5JcZdOExwOGD0CTD6BJxnazi0EffmpQxY+zoXV76Ec/kL1H6ay67eM8mffDLDZp6BGjBFRtcEQRCExOFwgEPmfXU//sUe5RkPYqB1P5U74YtHYdUT4G6kcfw5PO68kPvXZgJurpgzgu+cMp7+eeIlEA5jlIKBU8kYOJWiBT9AN1ax/bMllH21lKFVKxj++cfw+W9ozOiLY8wJZE84GUbPhz6j5WYuCIIgCOlO4QhoquoxC9N3FjHQugOfD3a8B1/8Dba9g3Y4qRh5Fg95zuOJ9Tk4lOKi2UP59snj0zwlqiB0Dyq3D+NOvopxJ19FXbObJZ+tZM/qpQyt+oLjNn9A9pZ/A+DpNRjXmHkw8jgYeTz0nyAGmyAIgiCkGw4nDJ2ZbClSBjHQupLKnbDuJVj7DFTuxJs7gFUjruOP6MOIoAAAIABJREFUlcfzxaZMCnMzuGH+CK48doRkgxKEGMnPzuCcE+fCiXPZUVbP82uLWffVSgZUfMGxtZs4bv1/6bvuBQB0bn+U31gbORcGTAWn3OYEQRAEQUgfpOfSGbSG0vWw7W3Y/AYcWAXA/oKjeDb/R/ytbBruShfHjOrLHxYM5bwZQ8nOkMyMgtBRxhbl8Z1TJ8CpE9hb8XXe2nCQ69YdpPrAZmarzcxr2MJx2z6n/6bXANCuHNTg6cao3NBZMGga9B0DzowkayIIgiAIgmCPGGjxUnMA9n+B3v4uvq3v4GwoAWBXxnhe5kpebJ5DaUs/pg0r5LYzB/G16UMkjFEQuoER/XK5Yf5Ybpg/lurGY/h0RwUfbSvj3p2VtJbvZpZjKzM8Ozn6wG4m7n+MTP0QAFq58PUZjWPABFT/idB7GOQPhoLBxnuvIiPUQhBSld7DoLYYsiWroyAIQk9EDDQbWjxe6htbaCrfQ+PBzfiKvyL70Br6Va8j310GQJ3O5UPfND7wncuHvun07TOSGcML+fn4/hw3th+FuZLxRxASRWFuJmdNG8xZ0wYDUNnQypp9VazZV8NDpXXsKK0hs3IL4/UexjqKGVdWzPiKLxmp3sKFt119bmcu3sw8fBl56Mw8yMhBOVw4XJk4nC6crgwcThfK4QKHC5SZffX030GvfolUXTgcKRwhi08LgiD0YA4rA+3utzbx1c6DZHgbyPQ2kOVtIM9TRaGvit6+Sgo8VfTzljOCg4xSpfRT7sC+u3wDeY+J7Mw8l+o+R+IYOoMxAwu5aFABvx5aQG7mYXUqBSGl6dsrk5MnDeTkSQMD37V6TmR3RQM7DtVzoKaZ1bXNHKqup6mqFOqKyW4uI99dRn9VQ56nibyWJvJUM3k0ka1qceLFhS/oPUP5yFBeFBqlFN/fsYy6zAFkuRxkuhxkuRxkuZxkZfj/Nz/7/89wBpXNznCSk+EkJ9N4zzb/z7V8znI5ZBFvQRAEQejBJN6qKNsK298B7bN56TDfh2z3ecDTAl43eFuC//e6zc/W/1uhpZ4fttThwBdWtCZHHg25/anrNZZt+afSUjAa54Dx5A47gqKiwZybmyEdI0FIUzJdDiYMzGfCwPywZXw+TV2zh+qmVmqa3DS1emn2+Khu9dLi8dLU6qXJ7aXZ7aPJbXzX4vbR4vHR4vEywOOjt8f87PZS1+yh3NNKq8drljG+9//fEZTCMOJCDLiAcZfhJMPlwKnAoRQOh8KhjIWOlVI4lfHZ+D78/exrRw7mqBF9OiSjIAiCIAgdJ/EGWslXsPTO6OWUw/6FMrKyOTPBmWVM9neZ784s4//sgpBtWZCVhyMrHzLzICsfsgogK8+Yb5I3AHoNICcjmxygf3efA0EQUhKHQ9E7N4Peud2fRERrjdurDSPP46PZNNz8RmCbMdj2f5PbS3Orl0brZ8v26iY3JTXNtHp9+LTG69P4fBqfBq/WaP932jBGdQT5pgwuEANNEARBEJKA0jrSIzqksFJlwJ7uE6fD9AfKky1EN9GTdYOerZ/olr70ZP0SrdtIrXVRAo+XNJRSdcCWZMvRxfTE34LolB6ITumB6NRxwj4f4zLQUhWl1Eqt9exky9Ed9GTdoGfrJ7qlLz1Zv56sW7LpiedWdEoPRKf0QHRKD1JBJ0cyDy4IgiAIgiAIgiC0IQaaIAiCIAiCIAhCitBTDLRHki1AN9KTdYOerZ/olr70ZP16sm7JpieeW9EpPRCd0gPRKT1Iuk49Yg6aIAiCIAiCIAhCT6CneNAEQRAEQRAEQRDSHjHQBEEQBEEQBEEQUoSkG2hKqZuVUruUUs1KqVVKqROilF9glmtWSu1USt0Ysn2+Uuo1pdQBpZRWSi2yqeMJc5v19VkXq9Ydut2hlFqhlKpVSpUppZYopY4IKaOUUr9SShUrpZqUUsuUUlO7Wrck6peubXeLUuorU7dapdRypdTZIWUS0nZJ0i0h7dYd+oWUvcOU/YGQ79Oy7ULKhtMtYW2XrsTbLskkxvts1OtZKdVHKfWUUqrGfD2llCpMrDbtsbuO01UfpdRgpdSTZjs1K6U2KqUWWLanlV5KKadS6n8tv5VdSqm7lFIuS5mU1klF6WN2lfxKqWlKqQ/MOg4opX6hlFKJ1kkplaGU+oMynvENSqmDSqlnlFIjQurIUkr9RSlVbpZ7TSk1LKTMCPN+02CW+7NSKjPROtmU/ZtZ5raU0klrnbQXcAngBq4HJgN/AeqBEWHKjwYazHKTzf3cwAWWMmcBvwMuBBqBRTb1PAG8AwyyvPqmgW5LgWuAI4BpwCtAiVV24HagDrjALPc8UAzk9xD90rXtzgPOBMYBE4DfmmWOTGTbJVG3bm+37tLPUvZYYBewFnggZFtatl2MuiWk7dL1FW+7JPtFFz1HgDeBDcBc87UBWJJk3Wyv43TUBygEdgKLgWPM3/MpwOR01Qu4E6gEzgFGAecCVcDP00UnovQxu0J+oMD8TT5v1nGhWecPE60T0Bvj/n8JMNG8Fj8CNgIuS7m/mnouBGYCy4A1gNPc7gTWmd/PNMsVA39JRjtZyl0IfAkcAG4L2ZZUnRL+Aw1R/nPg7yHfbQP+X5jyfwC2hXz3KLA8TPl6u0bB6HC8ns66mdvzAC9wjvlZAQeBn1rK5Jg/7P9Jd/16UtuZZSr97ZKotkuGbolqt+7UD+MhtQM4ybwZWzt/ad12kXRLZNul6yvedkm1V+h9NpbrGcMQ1cDxljLzzO8mJkkP2+s4jfX5HfBJhO1ppxfwOvBkyHdP+u8v6aYTIX3MrpIfuAmoBXIsZX6GYUSoROoUpswUU95p5ufeQCtwhaXMcMAHnG5+PtP8PNxS5kqgGShIhk7ASPOcTgZ2YzHQUkGnpIU4mi7AWcDbIZveBo4Ls9tcm/JLgdlKqYw4RZinlDqklNqqlPq7UmpAnPuHJYG65WOEqVaZn0djjG4H6tFaNwEfRjhu3CRRPz9p3XZmmMelGB2jT82vu73tkqibn25rN/PY3anfI8CLWuv3bepI97aLpJufbm27dKWD7ZJqdOQ5Mhej02P9jX+C4bFNlt7hruN01efrwOdKqefM394apdS3LWFu6ajXx8BJSqlJAEqpKcDJwH/M7emok5Wukn8u8JG5r5+lwBAMz2OyKTDf/feMWUAGwXrvAzYRrNMm83s/S4Esc/+Eooyw2n8Bd2mtN9kUSbpOyZyD1h/DPVga8n0pxgVux6Aw5V1mfbHyFnAVRrjADzFctu8ppbLiqCMSidLtfgx363JLHf79Yj1uR0iWfpDGbWfGlNcDLcDDwDe01ussdfj3i/W48ZIs3aD72w26ST+l1PUY4Zs/i1CHf79YjxsvydINEtN26UpH2iXV6MhzZBBQps0hYwDz/0MkQe8o13Ha6WMyBrgZI8zxdIx2+j1wi7k9HfX6A/AUsFEp5cYI7XtSa/2QuT0ddbLSVfKHu3dbj5EUzEGpezBCMvebXw/C8MKXhxQP1TtUp3Jzv2To9GugXGv91zDbk66TK3qRnofW+lnLx3VKqVXAHuBs4OXkSBUfSqk/YbjF52mtvcmWp6sJp1+at90WYAaG6/xC4Eml1Ila6/XJFatLiKhburabUmoiRqjRPK21O9nydCWx6paubSdEpyc8R3rwb9QBrNRa32F+/lIpNR7DQHsg/G4pzSUYgz2XYxhnM4D7lVK7tNaPJVUyISqm1+mfGPMjz02yOB1GKXUisAjj+ktZkulB81uZA0O+H4gxOdKOkjDlPbS3cmNGa10M7AfGd7SOELpVN6XUvcBlwMla650hdfj3i/W4HSFZ+rUjndpOa92qtd6utV5lPnTXAN+31OHfL9bjxkuydGtHN7QbdI9+czG8JBuUUh6llAdYANxsfs4ifdsuFt3a0U1tl650pF1Sgk4+R0qAIku4Heb/A0i83hGvY6DCLJcu+vg5iJGIwcomwJ89L93aCeBu4I9a62e11uu01k8BfwL8Rmg66mSlq+QPd++2HiOhWEICjwRO0VpXWDaXYEQShEZDheodqpM/AiHROp0IDAYOWu4ZI4E/KKX8XsGk65Q0A01r3Qqswsh6YmUh7eeu+FkepvzKzoycKaX6A0Mxboidpjt1U0rdT9tDdXNI+V0YF8VCS/ls4IQIx42bJOrXjnRqOxscGLHKkIC2S6Ju7ejqdoNu0+9VjEx3MyyvlcCz5v+tpG/bxaJbO7qj7dKVDrZL0umC58hyjHmmcy37zQV6kXi9o13HW0kvffx8gpE1z8oEDO81pF87AeRiDGhY8dLWF01Hnax0lfzLgRPMff34MwTu7g7BI2HOWX4Owzg7SWsdanyswshka9V7GEbyDatOk1VwmvqFGNMiVnWT6OF4CEMX6z2jGLgXI5QfUkGnzmYZ6cwLw93dClxnKn0/xuTJkeb2xcBiS3l/2uj7zPLXmftbU37nWU54I/AL8/8Rlu1/xPhBjMKwpJdjjAh3dUrsrtbtQYzMPicTnPI6z1LmdqAGOB8jPeuzdF+a/YTql+Zt93uMm/QojM7E/8PI/nNmItsuGbolqt26Sz+bYyzDPs1+2rVdNN0S2Xbp+orWLqn2ooueIxipwtfRlip8HUlOs2+RLfQ6Tjt9gKMxOog/xZhfd5Gpwy3pqhdGRtj9GOHRo4BvAGXAPemiE9H7mJ2WH2OqQIm57xFmXbV0X5r9sDphTIV6FSPb4UyC7xnWLJN/Ndv2VOAo4H3sU9K/Z24/1ayzu9LsR2wnm/K7sU+znzSdEv4DtTkpN5snxm9xzrdsWwYsCym/AFhtlt8F3Biy/USM9J+hryfM7TkYWVYOYTxU92DcNIangW52emngV5YyCvgVxuh2M/ABcESatF1E/dK87Z4w5W0x5f8vZqrWRLddonVLZLt1h3429S+jvYGWlm0XTbdEt126viK1S6q96KLnCNAHYz5Krfn6J1CYbP1M2UKv47TUB8OQWWvKvBX4LpY06+mmF0bG0PvM+0gTRgKU3wHZ6aIT0fuYXSI/xmDnh2YdB4FfWts+UTphGNLh7hmLLHVkYawBWYFhEC0h5DmBYfC9bm6vAP4MZCWjnWzK76a9gZZUnZR5AEEQBEEQBEEQBCHJJDNJiCAIgiAIgiAIgmBBDDRBEARBEARBEIQUQQw0QRAEQRAEQRCEFEEMNEEQBEEQBEEQhBRBDDRBEARBEARBEIQUQQw0QRAEQRAEQRCEFEEMNEEQBEEQBEEQhBRBDDRBEARBEARBEIQUQQw0QRAEQRAEQRCEFEEMNEEQBEEQBEEQhBRBDDRBEARBEARBEIQUQQw0QRAEQRAEQRCEFEEMNEEQBEEQBEEQhBRBDDRBEARBEARBEIQUQQw0oUeilLpMKbVZKdWslFqnlDpXKbVMKbXM3J6tlLpXKbVeKVWvlCpRSi1RSk0KqWeRUkorpY5TSj2vlKpTSpUqpe4wt5+hlPpSKdWglFqhlJoVsv8ypdTHZrk1Sqkms/wcpZRLKfU7pdRBpVSlUuoJpVSvkP1/rZRarZSqVUqVK6XeU0od282nTxAEQejByDNSEFIbV7IFEISuRim1EHgaeA34AVAE3AdkA1vNYllAPnAXcBDoC9wMLFdKTdZal4RU+ySwGHgEuAj4nVKqEDgL+C1QD/wf8KpSaqzWutWy7zjg7pByr5kvF7AImGyWOQT82LLvUOBeYD/QC7gS+FApNUtrva5jZ0gQBEE4XJFnpCCkPkprnWwZBKFLUUp9ChQA07R5gZujdiuBD7TWJ9rs48R4IJUCv9Ba32t+vwh4HPil1vo35ncuoBjoA0zQWu8yvz8X+Ddwotb6A/O7ZcDxwESt9c6Qcu9qrU+1yPAycJTWenQYvZyAAjYAb2mtv9fBUyQIgiAcpsgzUhBSHwlxFHoU5g16NvCStow+aK1XAbtCyl6slPpcKVUNeIAGIA+YaFP1m5a6PMB2YKv/wWOy2XwfHrLvVv+DJ6Tc0pBym4FhSillkfFUpdT7SqkKU0Y3MCGMjIIgCIIQFnlGCkJ6IAaa0NPoD2RghEGEUur/Ryl1DvAcsAm4HJgDHA2UYYR5hFIV8rk1zHfY7B+unN33LsBpyjgT+A9GyMe1wLGmjGvDyCgIgiAIkZBnpCCkATIHTehplGOMoA2w2TYQ2Gv+fymwXWu9yL9RKZWBEWefKlyAMSJ4vtba7f9SKdUHqE6aVIIgCEK6Is9IQUgDxIMm9Ci01l6MOPoLQsIgZgHWuPVcjBu7lW9ijsylCLmAFwiEoSilTgZGJE0iQRAEIW2RZ6QgpAdioAk9kV8CU4FXlFJnKaWuAl4ASgCfWeYtYJKZRvgUpdTtwG9IrVG3tzDi/Z8wZbwJ+CdwILliCYIgCGmMPCMFIcURA03ocWit3wGuwEjL+wpwO/BDjIdPjVns7xgpfS8BlmCkAj7Hsj3paK2XAt/FyHD1OvAt4CqMydeCIAiCEDfyjBSE1EfS7AuHBUqpYRg37d9qrf832fIIgiAIQqogz0hBSC3EQBN6HEqpHOBPwH8xJkSPwVjYciAwVWt9MIniCYIgCELSkGekIKQ+ksVR6Il4gUHAA0A/jLVbPgIukgePIAiCcJgjz0hBSHHEgyYIgiAIgiAIgpAiSJIQQRAEQRAEQRCEFEEMNEEQBEEQBEEQhBQhrjlo/fv316NGjeomUQRBEISexqpVq8q11kXJliMRyDNSEARBiJVIz8e4DLRRo0axcuXKrpFKEARB6PEopfYkW4ZEIc9IQRAEIVYiPR8lxFEQBEEQBEEQBCFFkDT7QlLQWrO/qoktJXXsq2qkpslNq8dHlstJ37xMhhXmcMTQ3hTlZyVbVEEQBEEQBKE78XmheA0MOgJc0vcTA01IGD6f5qPt5by57iDLtpRRUtsctN3lUHh8wcs+DOuTw1Ej+nD61IGcPGkAuZlyyQqCIAiCIPQoqvdC1S7j/2GzkitLCiC9XaHr8HmhtcF4eZohty9kFVDT5OGFVft46rM97KloJD/LxfwJRcwZ05cjhvZmZN9cCnMzcToUHq+PyoZWdpU38NX+Gtbsq2b5jgqWrC0mN9PJqZMHctXckcwe1TfZ2gqCIAiCIAhdifYlW4KUQAw0oWO4m2D3x7DnEziwCko3QmN5u2IelUmjL5+pvoF8P38KQ+efwJHHnkxW3xG21bqcDgYUZDOgIJs5Y/oB4PVpvthVyZKvinnjq4O8traYo0f14cYFYzl50gCUUt2qqiAIgiAIgtCNBPpyOmKxwwUx0ITY8flg53uwejFsewfcjeBwwaAjYeKZ0HsYZObhy+jFin11LF+/nezWCqYXtjIjp4Scin/DFy/CF0DRJJhwhrHfsKPB4Qx7WKdDMXdsP+aO7cfPzp7M8yv28fePdnHtkyuZMbyQX507lRnDCxN3HgRBEARBEIQuxDTQtBhoIAaaEAteN3z1PHz8J6jYDrn9YPplMOlsGDEXMnMDRbeV1vGTl9exak8VM0fM4s6zJreFI3paoGQ97PsMti6F5Q/AJ/dB3iA48iKjzoFTI4qSm+li0fGjueLYkbyy+gB3v72Frz/4CRfOGsbtZ0ySpCKCIAiCIAjphnjQghADTQiP1oYh9fZPDcNs0DS44DGYfE67DDstHi8Pvb+Dh5Ztp1eWi3sums75M4cGhx+6soyJn8NmwdxboLkGtv8X1r8Mn/0VPv2LcYzpl8G0iyBvQFjRMpwOLj56OGdOG8QD72/nHx/v4r3Nh7jnoumcNCn8foIgCIIgCEKqIR40K2KgCfaUboCld8LOZdBvPFz6LyMc0Wa+18rdlfzk5XVsP1TP12cM4edfm0K/vBg8Wdm94YgLjFdDBWx4GdY8Yxz3nV8YIZAzr4Zxp4QNgczPzuCOMydz4cxhfOdfX3LNEyu45vhR/OTMSWS5wodNCoIgCIIgCCmC5BMIQgw0IRivGz78I3x4N2Tlwxl/gKOvBWdGu6I1TW7+763NPP35XoYW5vD4NUdz0sQOeq969YNjrjdeZVtgzdOGsbb5dSgYBkddCUddAYX2yUXGD8zn1VuO5/dvbubxT3azcncVj149m4EF2R2TRxAEQRAEQUgQEuJoRek4XImzZ8/WK1eu7EZxhKRyaDO88j9wcA0ceQmc8XsjVX4IWmveWl/CL1/bQHl9C9ccP5ofLJxAr6wutvc9rbD1TSMpyfZ3je/GnQIzr4KJZ9kajQBvbyjh+8+tIT87g8cWzWbqkN5dK5cgCDGjlFqltZ6dbDkSgTwjBaEH4vMaL1dmsiXp2dTsh72fQf5gGHV8sqVJCJGej45ECyOkIFrDF3+Hv803Fgq8eDGc/4itcVZc3cT1i1dx09Or6Z+Xxau3HM/Pvzal640zMG6GU86DK1+CW7+CBT+GQ5vg+avgT5ONMMjy7e12O23qIF648TiUgoseXs57m0u7XjZBEAQhPpprjJcgpBO7PoBNryVbip6P32FUdzC5cqQIYqAd7rQ2Gl6z/9wGYxbALZ8bRlEIzW4vD7y3jVPu+YCPt5dx51mTeO3bx3PksASlty8cASfdCbeug8tfgOFz4NMH4IFZ8PjZRpZJd1Og+JQhBbx6y/GMLcrj+sWrWLK2ODFyCoIgCPZse8d4CUI60ViZbAkOD2SB6iBkDtrhTMUOwxtVugFO+hmc8ENwtLfZ391Uym9e38ieikbOmDqIn549meF9c20qTAAOJ0w4zXjVlRpz1VYvhpevN5KOTL8Mjr0J+oxiYEE2z95wLNc8sYLvPfslPq05b8bQ5MgtCILQCSobWvloWxkLJhRRmJsJXg845RGeKHaU1TO0MIfsDEk+JcROTZObA1VNTBlSEFN5rTWvrS1m6pACxg3I72bpUg3TgybJQgDxoB2+7PwA/n6SEfN7xYuw4EftjLNd5Q1c8/gXXPvkSlwOxVPXHsPD35yVPOMslPyBcMIP4Dur4eolMG4hrHgM/jwTXrwWDn5FrywXT1xzNHNG9+P7z63hpVX7ky21IAhC3JTUNANwqK4FKnfBxlehuTb6jvtXQn1ZN0vXs6ltdrP+QA2r9lQlWxQhzfh4WznbDtXh8cbmHfL6DCNlc0ldd4qVmgQ8aGKggXjQDk9WPwWv32qkz7/8WegzKmhzfYuHv7y3jX98vIssl5OfnT2Zq48bRYYzRe15hwNGzzdetf8Lnz0EK5+A9S/CxLPIPfXX/GPR0Vy3eAW3vbiWTJeDc6YPSbbUgiAIMaPN0WWHom2ORkstZEcYmdcaqnYbr2kXdreIPRZ/v7E1xk620EPx+WyjjCLuYs6rUuIVio4WD5oVMdAOJ3w+eP8u+OgeGHMSXPykERYY2Kx5+csD/OGtzZTVtXDRrGH86IyJDMhPo1T1BUPgtLvghNuMxCef3A8PHUvOrEU8esGPufo5zQ+eX0NBTgYLJhQlW1pBEISYaEu4HEfnxW9ZSIdHEDqP9iKBZ4lA7lcgV9rhg6cVXrnBMM5mXg1XvBBknK3ZV835f/2U215Yy9DCHF695Xjuvmh6ehlnVnIKjbDN734Js78Fq58k5+GjeeKoLYwryuPGp1axeq+EqwiCkB74DTRHPH0XCRkShK6jA0ksZEWvOBAPWhBioB0OtDbAs5fBuhfglF/AOfcH1hCra3Zz5yvr+PqDn3Cguol7LprOyzcdx4zhCcrO2N3kFcHZf4SbP4PB08l983u82uc+puTVc83jK9hWehjGeQuCkHb4QxzjCpUKeNDkUW9Hs9vL7vKGZIshpAs+b9y7+NcajnXN4cPaoHP7f4tioIGEOPZ8GivhmUvgwEo4588w6+rApo+3lXP7S19xsKaJ6+aN5taFE8jrjvXMUoH+4+Gq12DFo2T995e8oFZwp+N6Fj3u4uWbj2NgQZp6CgVBOCzw+QeXLX+jIiGOEVmxu5LKhlYGFmSTkynZGYUo6PgNtI6ikm2keN1QtQf6j0vcMRsrjHcZUALEQOvZ1JXC4vOgcgdc9CRMORcwRg1/+8YmnvpsD2OKevHiTccxc0SfJAubABwOmHMDjDsFxys38vv99/APz1aueUzx7E3zKMjOSLaEgiAItvhH4B0d8aAlu7OXojS7jfPji9G7IRzmdGKdrlivsJS5FIu/hOq9xlSYvETN1zfvU2KgARLi2HOpPQhPnG38wK54MWCc7a1o5MKHP+Wpz/Zw7bzR/Oe7JxwexpmVfmNh0Rtw9PV8Sy3h1qq7+O5Tn9LqkQxdgiCkJr6OTM8QD1pEdCDDXpIFEdKDlLGeEoC7yXhP5OLRgRDSw+g8R0AMtJ5IzQHDOKs7CFe+BGMWAPDOxlLO/stH7K1o5O9XzebnX5ty+C666co05qad+X8sdKzipn0/5pfPfYzPJzcGQRBSERtjIlqHMRlz0Eo3Ql1J4o6XZjS7OxEmp/XhZSSkHN1/7nWUY1Q2tFLf4ul2OZKyaHQCQ0jTATHQehrV++CJs6D+EHzzFRg5F601j360kxueWsmofr1447snsHDKwGRLmhrM+R/UBY8y27mdq7bczENLPk62RIIgCO1o86CleIjjoY2wuwvvo+XboHx719VnQ6Jsnl3lDSzdUEJts7tjFWz/L6x/qWuFEgAoq2uJXqgTF0pXXWMfbSvj3U2lXVNZJBrKjXdfIoxBkw4kYenJiIHWk6grgSfPgcYquOpVGH4MXp/m10s2ctcbmzhj6iBeuHEuw/vmJlvS1GLahTiufJExrnLOWfUtXnj/i2RLJAiCEIQOShIS704p9qiPp7d6cC0cXNM9YoS8dzf7KhuBTnjRmmu6UBrBz+7yBj7dUc6B6qZki5IaDtKW+rb/E2mg+T1oKXESkk+K3bWFDtNYCYu/bnjOrnwJhs2mxePl5qdX8cSnu7l23mgevHzm4RvSGAU19iRci15joLOW6e8v4t1VG5MtkiAIhxnbD9VT2dBquy3WNN3BOyV3DtqhuubA/5UNrTS2mp29RM5riYFYk4TXmyaDAAAgAElEQVTEfRZ9XqjcGehw+o/i9koHNJXwhww2tSbQGEllrKGG3g56eztCoj1oDeXBxmiKIQZaT6C5Fv55vvEguOxfMPxomt1ebli8iqUbSvn516bw869NwRHXCqeHH84Rx6Aue46RjjIGvnY5X27bnWyRBEE4jNhQXMNH28pst/lDHDXEbnDFGeLYISPQiqWDtbeikeU7KthbYXiNPtpWxsaDtSFyRcbt9XVuzlaMdNuAfflWOLAaqvcA4DTbTRJShcHrBq8nsUYBbT+nqNdBtAJ1pW2hgaG7plPii2R5sLSX7YfqKa9vjl62K9i5DLa+lZhjdQAx0NIddxP861IoWQcXL4YxC2hq9XL94pV8uK2M358/jWvnjU62lGlD1oQTaT3/cSapvfD0xewstu8sCYKQfJRS85VSrymlDiiltFJqUQz7TFNKfaCUajL3+4UKmdillLpAKbVRKdVivn+j25SIkQ518HTsE/2bWr28traYPRUhCze3NkJ9jPdBi4HWZBpWjW4br0SMBton28tZX9x9YX06UTGOzYZh6h8j9Xi7wECrL0u4IdOtNFbCxn/DxleN925kf1Ujn2xvM6RiX3MsyoWy+yOj059MGsph838MQ7fDWPQMMdbqWzyBUN0uxUyAU93Uys4yWTwexEBLb3w+ePkG2PMpfONvMPEMmlq9XPvkCj7eXs7/XXAklx4zItlSph35R36NqjP+ynS2su/RKzhU2w03I0EQuoI8YD3wPSDqBBKlVAHwDlAKHG3u9yPgB5Yyc4HngKeBGeb7C0qpOV0tfDz4+0laa2qb3FTUx5DUIA7Lo67F6OwfqAo5jduWwq4PYhTS4u0yjTXbwfgYR+hrmrrAAPG0GgOYPjujyB962E0WWoY537vFMND8XtBOhzh63Uab7PnU+OxpMebq2eoYhcbKzsnSVbTGEGrWUAFN1Z0+1Ko9VZTb/H6itkoCPEudPYTnwBpwN0JTFQBVDa0s23IIdzyDAhGE+HBrGav3VnVOSDt8HrwduX57MGKgpTPv/Bw2vQan/xamXUirx8dNT69i+c4K7rloOhfNHp5sCdOWomMvoeTYn7PA9zkfPvTtBKW1FQQhHrTW/9Fa36m1fhGI5el+BZALXK21Xm/u9wfgBxYv2q3A+1rr32qtN2mtfwssM79PGtY+09r91ewK9XSFwac1O8vqafFEDhX0exHadc3imRdiSSigfPZz6YyDJLAjVrYZyrZA1a6wRbptdRWHOefbNCo8ZgfU/15W19K5Z0tjhfF+cK2R7bL2QHz7V++FHe8Z78kmlkQ2O983Mll29aG7YvZHlN9JIqIGa5vdrNm6M2jwZmd5PTVNboo7nAAlWPC4DL148HnxV61SPBy0vL6l45lY40AMtHTls4dh+QMw50Y49ma8Ps0PX1jLsi1l/Pbr0zh/5rBkS5j2DDn9BxwYdzkXNr/Ec3+7q/tuTIIgJIq5wEdaa2tvZSkwBBhlKfN2yH5LgeO6XboI+L081o5ek9vLkrXF4TsLWlPR0EJpXTObD9ZFrL+rO6kq0ppG3WSgrT9Qw/tbDgV/6cw03iN4aILm3lXtaeel6bCHLaRX7k9G4vegfbqjvGMp0wPuVF/we7xy+kMk6w9FLtdDCV2oPLoRFaFAF13TnfHm1poeZ6vnOctlDBLE5bVNRhIf7cXj86Fx4HKmdr6ET7aX8/7m7v/NiIGWjmx6Hd76CUz6Gpz+OzTwi3+vZ8naYm4/YxKXz5Gwxi5BKYZe9hdKio7jqoo/89iTT3R+Er0gCMlkEEZ4o5VSy7ZIZQZhg1LqBqXUSqXUyrKyjs9ZjXZvsfPylNY249M6kIjDVj7TM+aN8d7VqVucpWOXVbUNtA4T4tg9HcAdZfWBTmoAl2mghczJ8fo0LWayjqBzu39FF3ppgpX3j/F1fg5aFz2HErT8wq7yhqge3GQkpgg9pK1xZC0UScZY5C/fDjX745KpQ3TWvolV5zipb/FQ0xhmMMnnNaahKWciV220J0Xmd4qBlm6UbjDmnQ2dCef/HRxO/vLedp7+fC83LhjLTSeOTbaEPQuni0HXPktNr5FcuudnPPLv95MtkSAIKYTW+hGt9Wyt9eyioqL4dq7cGXMIoZ0BF+oBsNkrsM0XJY6vSzpFlhDHjNo9FB36xL6cOxnzeoP1t3oZonktdEs9OY0HGLB7SafmQPnbq6HVg3vXcnIai8OW9fp0RM9oMB1svQQsw1Df4uGr/dWs2t0N85a6iIhJQoLOdaTrJAZD5uAa2PtZTDJpTxO6fFtMZcOJUlzdxH5zTml8TRxdl44MVr+7qZRlW8N4nrQXDWhHkpeCcjcb8zv3fd619bbUGXXHgRho6URDhZGxMbsALn0GMnNZsraYP72zlW8cNZTbz5iYbAl7Jtm96XftS2S5FCesvpWH3l6XbIkEQegYJcDAkO8GWrZFKlNCV1JzwEjBXroeiD5QHUg4qNt/54jQ+/Jvi3WeVZCxEu+6RCHlM9019sbP7o/jqlabGd4icbCmLWo12Bi1PzfWDmZJdRNsedNoExsydrxN30pzsewwadTDHCT4o/le3+LFXbWHvpVfht119d4q3t98yN7bFs4D2Rpn9jt/e6kOdop3vBc1a6H/7Eefa9cJT427KX7dbY5of4nF+sOJU/66Ulj/cjtPjb+WvuWr2PXVJ/Gt0xUiw4rdldE9l1HriTGhT6O7Y8fyY87L1MrV8Tq6An9odlcvCr91KWz5T1y7iIGWLnjd8MLVxo/6kqchfxCr91bxwxfWcvSoPvz+gmmoJC1Gejig+o0h6+LHmeTYy+CPbueBd7cmWyRBEOJnOXCCUirb8t1CoBjYbSmzMGS/hcCnXSqJ39tkjqpGX4KpfcZBXzQPmtaB1O7eaB600Ep8vrgNKWsWx658HGmI2gFes7fNs+Wx0zWMsQSw51CV0cEvXm1//CCr2OhI7iyrp7oxQiIU23ogy+VAa019s9H+mU77blhZnZHowb7ZwpyL0g1QZz+O0NTqbb8Iuv8a7GioY2NlVIPVL6ltmwQV7ISBtvkNw8C24mmFqt0Rd4v6+4FgYzhiiGOcYaul6419zCUYQnH4WqlsbI2v3i4KHd5TUU9DFIM69FQs23qIj7eVG/cNT3y/C4D9lfVUNrSilYPuXvciYgbcgGKWi8LT0jUhj3G2jxho6cLSO401Ns79Mwybxf6qRm5YvJJBBdn87ZuzAxNBhe7DMfE0OPFOvuH8hLL3HuDB97cnWyRBOKxRSuUppWYopWZgPM9GmJ9HmNv/n1LqXcsuzwCNwBNKqSOUUucDPwH+pNt64fcDJyulfqKUmqSUugM4CbgvqkDNtbF7nQK9QuOwvigd1GDPmZlx0XzeR/Kg+XeOVn+749QdhIaydhtqmty8u6nUfrFlG90N51f3zy/Kz84I/O+JkFI/HDGn+NY+mqpK2b5tI6v22IftVTe2mt6Edj4aMl1Gt8s//y0jjIHWtkcUYzNU7jAd/nc3l7ZfBD0Qktp97eNv++hJtrpYhn2fw/6VYc8HGEk1PttZEfhtRF8SouMhju3qDrNGobYzEGIlyADo+PncfLCWTSX+ReVjr6e+xQN7lxvZxeNkw/4KDtU1o0O8uc1ub9TBpXjYV9nIx9vL2V8VJcza2i6blhiDAAlGDLR0YO1z8MUjMPfbMP1S6prdXPvESlo8Pv6xaDZ9e2UmW8LDBsf829ATzuQXGf9k2dv/5uEPdiRbJEE4nJkNfGm+coBfm///xtw+GAhMzNVa12B4w4YAK4EHgXuAP1nKfApcCiwCvgKuAi7RWkeflKC9cYTGBHfAqkK9GxBUl7+PYvWCBDwA4QWyrJ+G0Zmv2BGx0xV2i7nPlpI66ls8tutIWeegBaTSPnsvkCeWddz8h9aRJDOqsxgqwcezngBrncH7R8pyF7TF50btWkbfyjWBsD2vT/PJ9vLAnLEPtpbx0dZyy0HaDAC/Me03WDJc9t0w5W6iV/2e6GF3MY7K23ZyfaZXIFonvLHSmGIBhnck1OiJMCgRc9e6k0Z8RX1LcAIKtz/kNXy9a/ZVU1rbTG2T0Y45Bz+zWXKgfcKMfZWN7b2R8cofmP9neFR3lNWHMUTiqLcLPGix/NaIVKLuoPFuepze21zKmn3R5236s75q5Qw6l0s3lLB8R0XU/e0wEgEFX5ut5u+uXfvZYb1H+TqxHIbN4M/G4lqWhWacDUEMtFSnbAu8fiuMPB5O/TUer4/v/OtLtpfV89crZjFuQH6yJTy8cDhQ5/8NR9/RPJb7Fx5/81Me+VCMNEFIBlrrZVprZfNaZG5fpLUeFbLPOq31fK11ttZ6sNb61zrExaO1flFrPUlrnam1nqy1fjlmoZwZ0ctAu9zey3eGdEJqi2HbO1C9zy8TAHsr20Z+/R26SOHtfs28lbuo3LWa5j0r2bdrM2DM1WrxeI0Otpn8wn+cZo+XlXsqLR0Z43u/IeRy2BzTppOqfB77jmccCyQbIY6RO5+tHl/A+NlX2dg2Qm4jU02jO+KovMfn45Pt5YYRGmp8lG3BF9Jpr6hrpry+hfUH2gzqhlYPod1YDTjN8+YxDULb8wj0K/uMwur14LXpSFp1au7Ews2BsK0oHfId7xlrkIHxvi1kFQp3+DW2YrcZOmeg7apoCElAEeyJqm5stR9UoG2Oo6u+BPZ9EbqxXfnVe6vaeyPjld9ioO2rbGL9gRq2H6qnocXbkdqMqqxLW5R8RX5tW5KRWP1xRihqZK9hRmsNFNvPn3SrDPZWNuIz587VNXvYE2bNRp9PtyU60v45aE5Dj9a2+1xFQ+yDOQGpteadjSW8tT445Dc7w/DQtbjDDSqY+rY2GJ6zKFk3Y8LXPjxy26G6oERFdoiBlsq0NsDzV0NGLlzwGDhd3PXGJpZtKeM3501l3vj+yZbw8CS7N+rSp8l3tPKvwoe4+z/refSjncmWShCEtCRMV8y/CLHpRbN1gJidmkhz0DSQ4amnV9mX7Ny0ms0ltWw9UIHWmnc3H2LphlLYvxLXrneDFpdu9RgHPGAucLv9UB3F1U2U1xtlnLYGWltvPLBVt4Uo+RyWaA9PHBnNok5fMlLm+ztfW0vrbMIPTcPT7WXZ1kOs3V/dbpufQ7UtlNe3GB1Ln7f98a1Gx9alZG03Jv+HZgNsdgdbJ1qDM8Qwt2u6qobWgGHms/NOWTviO5d1fMKf3/iLx/vTYrOeXkOZMRfNxivqD9GMOkc+mgyxhqCG1mce94OtZXyyPfx8uT5Va+03BF2nkeagRQlxDN3XsnZdY0sLfSrXoDzNfL6rIkjuuNomaJHEagpq458r7/XpqMfsX/4FVGy3be/91a0cqmumuDJ6cpMlXxWzdr9xf/Mbl5mt1bi9PjaseC9u2a1sO1QfCCMG4z4WnDwoxvPaaBk462hWzQ7OXxMDLZV54zYo2wwXPAoFg3lq+W6e+HQ3184bzRVzRiZbusObAZNQX3+IMc0b+fvAl7jrjU3iSRMEIQ6idcCC56jZdSj8fdaIOQ5C9vOPkGsNja0eYwS7qRI0ZLjr2x3F7zHbWFzNit2VgRHvaAZaAK8Ht13nOo5wLMODFr5D1dDqxac1+dk2GeBC9vOHFjabI+h9cjNRWgedpyoz+YdSKtgYMgmSvLUevG0d1U0H28L/tpYGhwL6tA6ct0ja7yirx9+qtssjRDgXzR4fW0oiL0oewBvsHY0LUwaf1ry76SAVXy2FXR+2K+YXv/M5Y+KVMfa5XFr7yG20z+AZtCae1hGWq2j/fcS5l5br31d9gNzGA/SqXB9TvbHUGXps66eK+hb2VdrPwfL4NMomrNP+eP7Q3bYy2kw4oyMtVE+b99/vXfN70HzmHLTqxvi9ZlasIeNbS+tYubuSrYfq2mS16uX1wLoX4aCNke6wREQcXNuxUNwOhkeKgZaqfPk0rH0GFtwOY0/ig61l/GrJRk6ZNIA7z5qcbOkEgKlfh7nf5sSaf/Orkev53X82S+IQQTjcifUBrkINsGB8Xg8ltU14zQWW7ar1d8cizUGzrz4kaYgjA42md81mq4CBv74Y56XYlVE+L+5WN7kN+4OViKPTooGK+uawncpDtYaXo1+ui6zmMF6SMO1izOEO3ubvPO6rbET7PO2M3EgJV7aWhjeOAiGOETv6xny4gFluZ8hGMG43FteyuaQ27ILA26zy+Q3njsTTmefA49Xg87K/usl2/mVMmRJjIcST6Pb62F0eEjpnk20TgNZGspvaz/exdVJFTuloP9jQrhKDOksmxPZJQnyBDeVmhGiW2+rVNeXY+QE0VrKnooF/rwljRAZoky3SwvQfby9n9d4qmlq9gYGKwH7e6B40CL5krOHC2jx/KsoAjLu5nuzGg4HPSpv3ucA6aJ0LebXO7fQPmjS1egOqZVmOzR5zvcbybe11Dw1Z74yBFme2VDHQUpHy7fCf22DUCbDgx2wtrePbT69m/IA87r/sKPuRSyE5nPprGHk8V1fcy02Tmrl76RbufWdrQrKWCYKQisRqoJmP3zD3ioM1xiKz+yuNTqhtiKP5Za9tr4ZNiW9Xu9I6UF92U2lgHpPXmRXYITSdvwqN0LKr2OZLrd3o/8/ee4fJcVzX4qe6e3LcHIFFxiISJMEABjEpkJREUlSgZWWJSrTpoJ9l2X6SP9uypd+znyVLtiU9BYsKDkq0lWkGiUkgKQJMAJGIDOxi887uzE7s7np/VFd3VYfZgQQSNNXn+4Cd6VBd1WnurXPvuWO70Db7NBQqOA3caKkUWspH236IGZV+4AIf+eJ+dE49hkidjWeu0sD0ghWiNu9v3DJ7kkosnTiKEbdTGEnIjIE9I+/HGLhYDEqhKASENpreJeJvvCk4BLppYs/oHIqVxcNDa4Y/g7FndI7ZGKaoMmn91WuLFuIu1XSUG7rtYFBQEGowd8LHuWn5p3CxDUWDv1LAoSd+hqdPzLok02VJ/PlqA0emSsD+n6Bj+nHEKwGlDMXrrsaadoPnDoJSxrpM7ueNSNsdmSzh+HQTpUAhxLFitUn8CribOjD6BE7MVEDMBtpmnoaqB9R8E1m5Fs773XvG8N/Pyudkoa7LDJr/G4TT2gCAJ0UREOu9Zhh6UzvIPPRzdMw8AVCKh56blHLQACBWmwEVQgObTWi4sW9sHsWq/wQQf4ekJp9yFi648wkFeJyqgH6UZ+RJhHoZOPIQC2/k41AYw79Y7hlH6KC92KDXgTtvBbQYcPMXMVXW8e47Hkc8quJf3nkB0rGzXMQvhAxVA97wVZB4Dn88/9d465Y8PnPfc/g/d+8PnbQQIUK0AP/3hKGzH/H5CsvpEFmbpPU7wEUPKIV//StKA95D1DbMOqZ3CEsVUFBMFmuSgWcKxljTXvvMmpumCaPqY1ByB+3gvUyEohl8js9xeOQU5nZ+B6pehmIVK1atkMP790/gqQCnjoOAOM6nnZMFZOYOIFIvLPoeNygLFyXUACFAtDaLaM06ps++scok+kfv8RjQ+8bmmbNhmlAVOM4Oz98zKYoVHeWGgefGgpVCIxpXifTvd2rhGHDqKWBsl9M//vfgvewf/26aqE0fg0kpTs1VUNMN7Bubx57RecdBo4BiNqwcMx8HjeegietMw66Vtf3QlHUvnoaDdmw7lMJxaHpZYooUiWWjODBeZH21QILUJi3neqJYBY0kgvtw4pes1hwEQY6JPVYbQv8P/QzTj/2bFarqA9OEMxNCQXm/RAJQPF+VAtKage6J7UiWTyJZHvUOgVJpfG6HplVzhCmTUqf8w+S+4FIFVqOjBUckhjtY+08V7PwyPxw75TDdTIiIgkKBeA/RI7+wPz9xfNauzWZWizAWZux9dx6bxTMnCzYbuH+s6FujUCJKA4OMW5mJcqFRYe+wkZ3Ossm9QGmcqYJa77o6ZYqdrdqGoYP2YsP9n2DqODf8I6qJHrz/GzsxWazhS2/fiv58kxdHiLOHTA/wxjtACsfxcfrPePMFg/jnnx/CJ3+6L3TSQoT4TcNiz3ytBBzb7jgoAdvzGeXZUhWPHJqWzIZF656J3QlY7hemR6iBYlXH9kNTmBkVwrX9HLQAx487FnytblCUphzp8smS5WwapxPiSEECztPx53ZDoTqSlTEQhbOS/vWgSjUdBVfoH2fQ5OFRZIvPoXviF9BU4t7Yx3ll14tSoGtyO7omt7sPbZ+vaH3W2o/vyP7sHyti+/4R4Nk7kZg/6qywHIG794zh0FTJGl5w+JhqnQM9oO5YvsAcjFJpDocm5zE+X3U6ytUYx1kuVOPETux65L9xYLyIkUJFEl4xTNMJX+TOik8Il0urg+HIg3atrMlijRnWp8OgNcqgYOF0ouNHqIHdI3PMObHbo3b5A2rlEyXKo1CMmr2veC+baF5Tlkzttdv1HSjgywjLt5f/eKUlrmc8O/kENN26/kTF+HwVY3NVVBsGHjgwiR88PSq16X2+W7NFeDizIsZ/uth5arfm06YQ4hik3kgptVROnTYINQFC7BBJAEDZYbZGChXcu3cc89UG9j3wbTz58+8CAB45NI2Ts2UcmVrALw5O2aJGpwXNYk0VzS8W1d155yN/h3EhmaASK2YDdcPEzhPz2DdWhNJiFFzooL2YcORB4OF/AM57B+jwa/CR7z2Dncdm8elbtmDLkvzZ7l2IZhjaBrzi4yD7f4y/6f4Z3r5tCF988DD+8od7QictRIjfKCzyvJ94jEno2+pgAdtzo9dmKpztoq7aWb7FjPmalkMRHadQMWowZ5lTRcAENYIcpLpu4vtPjeDwZMnqq5xb19ANW3QDAJ6t9WC0rASEBPqDOVWU7dOQw/uo7RRQ2+AWZ8cJpbbQyX17xz1hkraDJrYpfFYgn66GYUjfZxfqoGDOgWgUJ8qjwjV0rgOxwpz49YzPOQrAisX8paZ32QyKaZq2SqUNj4MmOCncQRb6aNeCEhY+fWwSU/MVnJgte++H2WMAAGOeMTW83ttk0QknvG/vmH0unRBHr0npW6uv7FfX6jQcNAGiPU+oiWMjo5g4ultqz1HTpIBeR/vMk+iYetxer4s5VIvdlyas3CnOMhrAzBHpeO5C6ZF6AepRQUBFYLooNZ3wPhfHIyLWcO5bSlQ8engajx2Zxt17xgW2KDjEsSUzxDShFY745I8FvaP8rgm7B4jrPIqhqKykiDcHl93zzrhPznlDAbcfnEZZyJsTz1mppmPHUcc5jtQLGDj5YygGe2cEnYNivI8Vqm8bguddQE2buRP7G6tOQd91J1Mv5ddTEZ174foZOso1HVTRcGC82LI+UuigvVhQngHufD/QsRK49pP47H0H8f2nRvHhV63F9Zv6znbvQrSCiz8IbLgZys/+Cn+5aQrvvnQ57th+FB/7/u7Tip8OESLE/1zM13SUyhWW3D9/CsVqA3ftHnOS8TlzZuUlUEr9i6ZyCX2fUJxcPGKts+axT/P1QnwMLgqAgPUx0pi3HYiGSXFgogjRcNEaRUT2/SdQK6FqGf/Hpi1DnyiAFrf7pPvkQukmYeNrscbQidkyAIquiUeAfT/yjIaPiVoz0+0zQn4JqCNi4HOiFMJEO+TwMiBhSfabgjVVrut44tisYxBTihOzZUyXaiDUlMQS2meeRKqwX2oTABRVs84BW5IWlPsUauDwVAmTpZrD1hk1mHWZFfCV3nejXrLPr9Mv9ne6VGNhiZ7eyWgm9FBvWPcvKIipgxCgolPUdXkfXwaNY37UdkoXvYldtdeYU0xlN4Ya6J7cjsj4MxBzvOTxs8+aXraNe/Eam27xGkKATC8AJkxSqDSQm9sn52SO7AQqjgPFCzNH6nNIlEfQPvM0sDBhDZNidLZkP1+sdh6/P/2HXm0YODXrHy4psX9GcIijH6K1GeQsRhUAMHUAsYmnkVo4Lk8sK67UGkKknE2pP4Q7aPJ98LBQ4kB09PnED2PQ5BDHUyUfBVXXMZvdNukSm2jomN4JreEv3lM3TOw8NounTsyhXPcym0cmi9g7Nm87aYcnWTvx6gR000Tt6KM4seMn7HxZ52nvqXmn5h6lgMnqLvLwz8ePtlYDMnTQXgyglBWjXpgAXv9l/GDvHD597wHcfN4Abrty5dnuXYhWQQhwwz8CHatBvvsefOxlWXzgipX45qPH8ad37mpaGDVEiBAvDTx8YAIP7j7MEs9PPY2jU2XUdAMjhQqqDQPFagOjhQp0y+g+OVNmRW8phSIUJSbUy3pwaArxzUd+bt9uW0VwpFDB3tF5X3aN+IVYUSdHJ1EZ9zmssyC1cJxN0RdPebYpVHT8uLYRxa5z7WViMWYKK4zJNIDjj3r6JiJac5gWQoFowxtCRIUwNUK84Wnx6qQwFq/DwebsnbHNLtRhmnBycPSqh9coVuUCz3XdBKEGDJfjpEqMBttWUb19dIr16h5nPXLsF6B73U6pcJxEHhDEJTiDljj2M3Z+De/s/9h8FYopFNKmFBgVnVq5X37gBvhUsQ7FulefGZnDgwcmUa7rGJurSuPmhveJmTKePjHLGItj29E1ye+BX+X3Ud6HTWYIzBYbhPzbK0x8cCEJydkStn3k0DQTVbGEQ56bKGF0rgKFeouQ++VpdU88jPaZp6QtZxbqePLYNHYcm0XdMHFytiwwaP7wFmr231LX/ZmloD26Jh9BunTUWWDUAQooRh06L2IPOO8Kypxxp1ET9+0dlxsl/gxaMETnmUi5d4ZYN9GCx0Fzrc/MHfA4Y9F6AT3j3hIQAFCtG0iUR0FBsXv/fk8+bKnCnse6FTJ8eNIpC0BN4MjoBMaLVebcWQ7agfEinhVyH2E0JELNCe9sjtBBezHgyW8Ce74PXP1RPKEvwx9952lcuKwdn7x50+LFHUO8uBBLA7d8E9CrIN95Jz7y8mX4vatX4Vs7TuDD33k6dNJChPgNgGOcyM/7PXvGsWdkBqNzFRyfYLPs3NjPF3ah79Q9zsuMLqAAACAASURBVMw/NyR9WAz37wK3WeYObsfe0VmYJsWOozM4WSj7vnPSpSOewrw8TA8ANL3oCZHKFJ1QvMCcI2ri6EwFOiI4OGcZaqByW4SwPB+rjbphupT4HDjGuwzTFBLthZwX4hNiJ+Z8+YVpiiqOxWoDh6ZKTK7Aajd6YrtrDyq4XdT+n1DDUzpAzKcRQxzdSsz2OmF/xWT3xYGJImPbBIPXFPPL4nlJhc7OyeIOyolHWfvURNKSFq80DHYsgWXCtLdETFNSy9p3rtKw7wcKBQt1HffsGcdjhydYUeuGwP6ZBp44NoOGSRnjCth5VSgxhkk3TLtWXTPwMYnPAqEGTBLxGO0ig3rMyuOT8rWEkETRKZ2fOIpyXbfv83Ld6+w6Bwmu2xXRS6jrJko1HQ2T2udrxGKG7fvIalIxqvZ9ezowBGf8V8qsKE3YbpJJKXaNWBMimuUoHduO3rH7hR0oSjXdDiVkJS5ak9kX2+Dbt9JlKkyC6IYpXS9i1pEtPoeuyccWbYffNYZJoZrs2ikNb86cO9ogMbETilEFoQYonHvLHeIr5dKZhvVcnt5FCSUBzzamDwE//Qiw7HKcWPdevO/zj6AvF8cX3nY+YlrzZNUQL1J0rQFu/GfgO+8A+emH8aHXfhaaquBT9xxAw6T49JvOgaaGcyMhQrwUQShFrDYLJOXlswt1mAJLNjZfQblQhBFn+cVcmY1QgxkdliHiF45IiKSJJ82WD4zchfm+VwGUILVwHDXN31BKlkcsFoUZpVSYuyY+SmOpheMotG1i602DHdMd+kRh50qJM+GUspDBCg/zVBTbwD88WUKppiPVMBCPOL953mR/pz8/fGYUmbiGq4d7fNe7QUFRqRuA4t0mUhpFvrAHxZSOk7MOE8V9KBMUCnXGoph131pPhJqshpQAkzg1lBw1Q3icZl7rTKGig+YwadWGAU1xzgcRmNYgS/zEbBnFqo7aqeeA6CZk5w8gUzzktE8bTv5eQBvNTGxu1FIAxLQYAqKgc/IxKEYVEb0EaO1QFygQvwRRjQDP/ifaZtmDMVOuo6+hwzaVLSfz6ZNzoKBQ22exuicTqFwt8i0OA2nCVCKSC01AMWkxUBG9hNFn7kUE8nMllU0QHICO6Z28EfnYRLWv/UihjGw8ggy8yooinptgjuGStiQsHpmdMp+Jg8UcDGK9R0xFk5wCMZzYfUmVhUnASACqBsWos8kgcWNCgKqlWup2rsoz7F/xFBSTO6JxGCYFMet2jbl4dQIkxfvYGoNGqPDkEkW6Ln7h3VSYxNAlZtQQnsegd4F3udstbBimw54DUHgfrM1ilQlk1MPe1gJNOhbiGJwnHIzQSjybMBrA924F1AhK1/8zbv36E6jpJr7yjgus4pkh/sdiw03A5X8EPPF14PEv4/euWY2PXDuMHz49itv//UlPnH6IECFeKqDIzju5R/GpXRg4+WPmcFDDNjqi9QKquoGFumzIdE49zgx4y9iI1byFl4lC3DajhPjoo8jN7UO0XghU8wOAeHXc6jFwZGpBMnCamRMigyYbgtSTbDRfYcaJY2gTUCi2A8oFKHjo0rHpBRybXsCOI+5xU2c7SlGs6pajI6jNuRg0zkhV6jw/zDuq+PiTiNZnUa7J7JfepIizM2beJ3YstS6HuZlCyKVD+FGs7ExLw6I1FpKliManmpT2FQ3e1NwBsTfSMfnpN9QECpU6CiSHgxMlaLpPjS3q+SB/b0LDROtO7SuF6sxRIgpitSnmnPFx1CqIV8ZRrOqoNHQkyyfBrxn7HXSHrLHvJ6YKeOJYcxape+JhEKNmt6AaFWbgu+9J63uyPIKIHf4mOmgCO0lNVBuGzOK57ivLLbTKD1Sxv0lxcjcUheddUYv9o+CuMIUlKGI0qZ9mbdl36h60ze6SlkpMoLBc1ctIjvwCGNmBkULF277ooMLLftUNE/UD97q7gLt3j6J/9B5ki8+xRUQRjhx876SLR7zbUVMQ/GHwZbyFvo1bBeq1xgIGRu5CqnRc6Ie1vfCm9GPI3Ic4Mes+N97wU11LevvKN586iPzsLgAETxyfZSUIjAZ7NVKKWHUSnZOPtkRxhg7a2cTPPwGMPgHjNZ/B7/54HAcnS/j8W87Hqu704vuGePHjqv8FrLmOMaRHHsIHr1yJj756HX66ewy3/etORzQgRIgQL0lMzZcxd3KP/Z2HrUlw/VBH67PQTSqzM6acl+QWd/D7redMnd5CWLWTa2JC1StQjarDdtlHks2F5yYs1UaxeWra23HJez4jLuaOUKLixExJCm0sVVlh26dOFPDUiYLkrIiDZOIH7NywxHtHJASuGlb8fB+eKsGg3mLbxKyDWKyVW/qah86ZbnsfXvfVNCnaCrvRNu4Kh/Q1MClSblbIEsAgAoMmOmSnRCl8CGlS0RQ7ho96XC3aBgDQtRQUo+4rkmAzFO5+JjtBKcXRAJl0sX8G0aCYDZQbhi2CIEI3TXRM70C6eBgHxuQ+2LXarLZE9cP+0XuapwRw1qwyAz7mttld0PQFzCzU8dQJQfXQWq8EhCFKh6GsRuAD+ybE0eLAmFBPDSYIpSgFFENuBgUEiQoLNSWE1exzHBGK7PzBRcMD+cRDosJYu3hlAsmF44hNOHmEnBXsHn+Iif6AAsUx7N67z+P43LPrmC0qQin1MFfPnCzgmZMFzFTk8XrDMOVw0yDk5vYI3zizLEy2uNZJRxDa5WIs0ToT3eDn1X5XEYJlHc5EB6k515CCTQ5NucKr3Y+CH4tnkggoYTXN7OhZvv/ok0gtHIdisoiJg+NFKfS5ffoJxGrTIHTxYtWhg3a2cORB4OFPA+e+FR8/vBr375/Ex2/ciMtWd57tnoU4U1AU4OYvAh2rgG+/HZg9ilsvX4GP37QR9+6dwHu/voOF3YQIEeIlBOcXfnTKJeneYtjPiZkyag3nB1xxiU9EVCLZMpS6HCCByQqoV2xD19K2oUxA0Tv2M6hG1bOde8YYANAoQ93zPcQrrD6RHSoFL8vkmKAEpQbF+MQ4jggOwCOHpzFf9XdQeN8Ai62yDFg2ZnG2XIZo6JomRb6wC/GKI2qgGjV7H9XF/Iki4EF8IrGNMwrFrHucYaI751Fk0MRDUfs//xw0gOU+eYz2/FI0TIqaIQu+2Mexc3sM9I7dJ7FaXrjGF0tjeqGOci3YiLSvAVQnB83loLHQWYbc3F7hXmQf7PwdakI3Tdvgdg6yeI+JUQNVI9K6Yk33nZgQQ0iltgTH0LCYs4W6MClCFMyLDKvFgJV/hUlWE1RiM9tmn7bZyFbzxhTLuKdEg9ZYQMf042ib3SXZE7ypSGMeHdM7WWUGU0fH9ONIlk9I7eVO3o9Kw0ChXPfc6YZwbio155zo1ERubq+0LSUKxuZYKG6rOWiicyq/Kfzfl37t8meF33+UKFD1CiKNeekeatR1dpIphR5rw76xeRR0OVqNUoqGYeLwVAm6YdrCSe53AKGuJdYXt3pmZm6Pb1kJ92SRH0IH7WxAkNT/t/bfwR3bj+LWy5bjty9aerZ7FuJMI54F3vzvbIbw324BKgW87eIh/O3rN+Phg1N41x2/tEN8QoQI8T8f4ux0XQyTChCpENdz7Dk1j6n5iu0UJcsnkSs4s875RBRSaB9kw2CuIuZpNDeUyok+JwenSf/qsQ7nC/cwFiZBKbUZkkK5KmayWW3C6p+ze7HmY9hSiuL0ODQ7TNC/FpNBTfs8UgqbQUuXjtj1jhzIKoqJyhg6pncAADLzzzFlN7mbArxFjH06DaAZS+lymgEQQ/eKhFh/RQfCPXPvMVZ7N2HnsQJ2PbsbYs6QbTYKYjOLGcvUvZ4G1c9z+sD6IxcW9jho9n92sxLESQWu+ihC8ynoSynF0ycKNsNLXXXp3Gj6zHm3xv6RSUTqc/I5U+RxqWYN7TNPyXmglGJsvrZoZMyx6bKdx8XvA5ndbCH0zXZIFImJEVlv9307XqxipMAcw9TCCRAQO5VGoQ3sHy/i4GQJc65C7mXB6TslXCM9cObHmRgApcjP7oKqBzOxHMQvRNmXgXb6E6tOepaxBQp6x36GaH1eCnEslCvoH/1vdE88hLmKgVqsA6YqO2gmBWbLdcws1DE6V7FLj0jN87BUKpxnCoBSHJ6yxkqdSYgdx2Zg8LBW+/ou7sCGDtoLDUqBH9wOLExi5wX/Bx/76VG8fF03/vT6dWe7ZyGeL3SsBN70DSYI8623Anodb7pgCf7hli14/Ogs3v6Vx9jsc4gQIV6yiNYLaJ95wrOcgCI/u9sbSkMNGCoL2cvOH0C6dAQAMNiWBAiBY7syk9wQjBmWP8MLHS/eN76NXzgPX9OI+ITeGw3b3EguWLPynEEjzvh4P/l6PzYuUzyE+oF70TPxENvMZZxxERXWV0vi3RWepM44IhjMIXbGc2zGYS2itRlkiget/vk7YkT0fwNt5ubGtOO3OVLvsendLoEX7siYIKYO00daHACyc/vlBUS1jz42X8VhS53QZpasv8lKc/EKdmhvECeKp7wspuSgmaBElkX3Ox9S9KA7NNQW9/A/j7pJMf/0D5nKtYXZcgMNSXXR8D0uR9fk9ib3NQBqIlrm5SJYO9m5/ZJIC5QIJru2SbuxsEEH5bqBE4WqLQbSDDb7aHWLlymQciqbwBb38Qkp5fA7I6KDlY6pkgPAHUvnPcL6EZRf5zdxkZ0/gHiVhYYSaiJan0Vq4TjaZp9BPhlFcuE4EoZzfiIKgeOoUNe9BPhVdBaZ5c6pXyK5cNK+Lx01USvsmcgpsYQaINRApFFEwzCsMbqPSRG1REImijVMzVd498SNpEkiCKMIsuVYXrHzMiHUQDsXoQlA6KC90Nj5VWDfjzBx0Z/gnT+tY01PBp/5rXM9M2ohXmJYcQWrkXb0IeagU4obtwzgn958LnaNzOEtX3oMs37FakOECPE/BlSgDE7NySqE6eIhQaBARmrhmGcZU6STjfULl7fj/KE291EBUMlBC1J49EMjmoVJKXQtHcigeQwnW8pdtw21iF6CVjolHF0MEgSWtqec9nwMy0hjHjNlUZ1QNs64g2oIjtcTx2chjVbqpleAgqNr8hG7DbuXfrP1IDBM6lu3SFOIbaSZSsz3OA7rR211S4UQ3/I53Hg0ib9qoacGnGB9npwt2/XTHJ/wNISoylN2zlmloYOWJjH97M88m8Urgpw/NUChok5VaZkIM4iJ4+vtLlKMzXsZtPlKAwdOnILRqNliN57rZOiA/qv9dipGFfnCs0gX9knL47VJWU6eENRj7Z79RdXPus7yL41WZkQs8GeWlxoYm3fX3PO3C7nzyBi0gGd2ESKOApL3ElH9hFCa7G+H0vpvxxlWgBUFj1Un0Ta7y56AYYcndqifU6ja00u5XVduatvs0/a7gTPQ3OE1qTwK/swzhXQfhxBeXku8p+UabGzSJYg9d6vvuuu3EUoRaTR35kMH7YXExD7grj9DfegK3PzEFiSiKr7yjq3ehOEQL01seTNw5Z8Bz/wHcP8nAQDXberDF956PvaPFfHmLz2KyWJwLZUQIUK8uMGV33Q16ZGJp0rEbxeovup6LFHf7aAphDBFsLkTgKUkRywjWLQLTUrlOjxNUE30orDkapQTfcFMA2HGjWLUoepl27AxGnWJMaCUCuyY46D15eKIamw5JRrgYxi5895SEX/zxDTlUFFpnNJs+eKhfeI+noBKyuzX8WIVE9Z7WVKHI87svxnEZFjd3Ds6h18cZKqUvnOxFJbcugkqlC5wC7PI/Vbgdx4dw7n52DvTjlNJKcVsuYGpUg2HJxdQmJnwhN4rhKB9VihmbRnU4n3tNp49MY4ucKOVsVHBYz0wXsJTJwuo66ZHFl2ZO9ZCUKAMXsIoUzzMiq6fAdQNPwejOdxGOwCYatyzzBZTAcHyzpQQ4qgh6Py2Iusu3j2K+32xyOuDd11pIi/Pn03VqCI/zmoairmeCiHoGb8fxKwLarXCRJMfg+aTR8i34+8QTci3FIfFc/8UAvsBd78n3aJAYhFxJ4ycsWG8ZiKwWCg0ez9LCqPUXHQSJXTQXig0qsD3bgWNJHHr/K2Yqej4l3degP58YvF9Q7x0cMUfA1veAjzwv1mBcgDXrOvBV965FUenF/DGL2zH8enFJHZDhAjxYoT926v4GOwBP8b+wgWW4e9y6ggBcHIHK3wqhDhOlmrSzD1Tl/NaWDUxj0zA7ikTbnl8GWxdz/gD6B37uT07XKu6nFDqbOvUCqPSLLuhRG0GLSJYd44inDXrrvifL4NSdE2KaolBM/i0JQeNWGFOfsSH+5RQgd1ShNl/LUAWfb6mwzBNKY9H9bFo5yp1xqBBVkKk7jpzFmq6gVLd9GcAREaiCbihXI+2gQJ2iCTgFTpg/ZaPpVADlBCJYXCrlFIAzYQYOWPaOfVLf4fSMno5g/nMSMEucG2jcfq/l3wonHlZHGwHsfSBGw3DdMJVBVQSvYH7iPdcPZJjyxS5dt5cpW6H8lIQaAqx1SjZBI73BM+U65gsNmcVCSAxuYXjz7qY4EUYNOuv0uLzZ/Pq4iSK9Tk3tx9xTZVUIevRNt97wlcJt0WkFo5BJfyJ5+Gkcv/LdR2HJgUHT3g/cxEj4qN0qZtUKhjPFSU5nDqIpv13sUmU0EF7oXDvXwDju/DZ7B/i4TEV//Tb52LjQO5s9yrECw1CgNd+BlhxJfDD3wcO/RwAcPnqLvzrrRdjttzAzZ/fjt0jc02bCREixIsPhmkJWFBvLsnpGBbc6HU7aAohgFXLh4Dn7rAfftEJCFKXm8sNQ9dSwhIS8FmGLVNuhVZx40N3qUtSiMydILktNG2qUYGJ8hqXusaM4MjcUQDAfGa1tN6kVM4PEmfc5S2ZitsiIAQopZf5MA5eToeC2KFgor/S0IJL44wUqlK4k5tBo5TlxxHKFOPEEEeRsetw1Ua9b9+EHcolQm0UPWUZ/MDD63Q14b0MPreCW7AjVptiZ8hmGBT7upSTA0yG3FoT2Acf7+2cwbzwLdiALScH7c+tMGjLO537vjsTFJIaAOsGzpzzWpTSy3w30U3qy6CJ/XTDtM7dUHsSisodc3k0tuiE0Beu4mgSNTDE0S6d0QTiFc3N7RGKULcS4siO6y5PIWwh5yxaf0Wmzl5mNtCWYu86O7fLr4g6pVL9vVbgDidWFB4a7LCSEVXxhHja+9v3NxVYZa/g06HJEsrV4MkC01WHMTe3z1ctV+pr07Uhzgye/S/gsc/jsa434NPHVuAvbtiAq4d7znavQpwtqBHgTV8HOtcy0ZCTTFXs/KE2fPcD2xBRCX7ri49i+0FvgdoQIUK82MFMm3qUGZrVeDcA5txk462Fszu5TX6CEcS1LfvrDZfyM5zkGeOx3iucXjcNzxINGgduA5sxAvJx84Vn5W2UiH0sPyE4U4kiXhnHAKzZaFe/mqX4iEwdodSWAS9mVjXZx3LQXGNx5+gAwOq+PFJRdg2JYOSVMisC258oOjXMtEbJE0rmHNVkeV1C6KLI2PnlrWk+0vnxwiF0TzyyaPiUfb/YjhSDblAcnXIMTV5gPChPfqbjXEx1Xgg9krLZ4GJmJeZy64BEW2vekwBCgOHeLPvcZAyz7ecwxoff/4F5gAxtySh6MnEkIyq6Mt4wwmbgt0ZEVQL7pBuM0aQUqMYd+873ubLLRLCvhBDAYk7d7UvPGPHL+WrtBDciGen74gHQLTJogf6Zi8Em3u3jETbmROUUVIXAEK6hwySbNmOYL+zyMFOLwf282Qwa5Ywn8YZ3CrAny0zYYdr5wrOIV8c9Uzi1evD9alJITl2s5pXe9/R90S1C/HqYPAB8/3cwkduMt564Abdethxv37bsbPcqxNlGPAe89btAqhP45s3AqWcAAKt7MrjztkvQn4/jnV99HD96ZnEFrhAhQryYYIl2qHGMDL4a5WQ/ABbK2MwQAJywM7sIsEsCumE4oYgUQL6wG20zLC+IOy7coPbLQaMuWXRDE4U7FBd7IYAQ35l6t4S/aYcNQfhLJeeCOWjM+PLLwQEoLuwldm626Qrz80u294M4O93M+SSEra9Y18neh3qNu/Z00jYwVeKEZYphiY1I1m9IAIBM8aCHceAGeKZ42FJGVO1r1GoeIWdFqw0DBqXQ9FLT8Knh3iw6sikUMytBCZGcgIZp2mxibzZuj9ePYSAwYWgp1OJdEA16SjQspJfB6Fp/2vlhCiFIxzTEtWB2aKz3Sus4Vl5jJOV5VvzaXdKexPr+4MilNd0ZrOj0sqE1gwu8AEEOkW5SmyWvxjsx1XkRJrsugZ+jw7QvieCgwXbQmoddEmnSgFhOfStws/F+Aoby+sUcNB6y5w/NqCA7v9+zXHwXxIQ805iqYrrzAvt7LsmctYGRu9B36l6kSkeRWpDrt7UCd0QxJ9A0fQEemUcfcCdTN01Pnplbor9ZSROT0tMT7kHooD2/qJWAb70VNURx48R7cfWGAfxZKKcfgiPbD7z9B0A0A3zjJmCSvcz6cgl85/2XYPNgDrf/+5P44oOHFk1ADRHiNxWEkNsIIUcIIVVCyE5CyOVNtr2DEEJ9/i0I21wZsM1wy52ijkIYn2Ulpu7LgnRbs/nFzCqs7WGz3HZYDVGlWdpMzBHY4K+EeG3SOg5b4DAdQYZH8HK/ulNTnReCM2hD7XIODjfsOavE6pJxMRD/I4oMGsAKZUugFBoM2zFwG5Z+YXH2cSRBAJFdYitMonmYBNZXFbOd59lsp7XUe6aI4jABCkHb7DOeLUvpIUx0Xwa/80yJ5jG6eChasnwSmlG28hd9GDRPa0IbsQ7oWgq7R+cwV2FOglsxVHQcY5qC3MbrsHzDxQAU7B71D6kfbEvaAhVxH9EWXgbCDdthpW5Jj8XBneKqbsAvxHG6Y6s9sUCJigMTRewcKaMVTmgxZBMRtKeinnDS5yassGJCAhk0w6RQaAOUAoYaRy3eiVXLhnDeMm/eJ6Hs/rbDBEGgaIuz68ytE8ZJKTS9Erh9WhCgM4lbpChIf9E5lh84yzUyy44bFOKomHX5HrRuBJGJFfMx21JRGIJACnFNqsSrv1pEkbsAvZcJbn4eeNhuw4fuN1ysrVjKww3TJ29tMfX20EF7vmDVO6PTz+E9Cx/EkmWr8ZnfOrdJvG6I30i0DQHv+AGgaMDXbgBmDgMAcskIvnnrRbh+Yx8+8ZN9+JPv7UJdP73ZlxAhXuoghNwC4DMAPgHgXADbAfyUELI0YJffB9Dn+ncYwLd9tt3g2u65ljpFKTMyuWFgGRqEmhZb47At+UQUfbk4Zts2YT63FskeFiqXLJ9kTRHV/lGPaSrSUVF8RDYYuOPS9EffU7dKaI0ovg6k40BRT2gYP2Y+yYw/U8q9CzpOBI7p4Q2dJKBQiLOMh67lEuIxWC0z3i9nX+eYYs4fP+eGlpCcHl1Lo772RlAl4i0wTIFGoktepqj2ESTDz/pci3WinFqKRjQHQ3WMN6beZsBQ44vaAKJTLjJoi5FpzJEOhigQQ6wGOXvYDFzePqopqEfbMNO+xVknMrDWmelMRR0G8NecWGyfedKzrJoQwwctx1uJBt7X/bkENvT7sJouiHlpy31YNMAindxKlRbEeQPuaBACwEe9lVAKQiAxaFW9tXNFhPuHgErCGhx2gfuokM/oIzjTXBcoYKW1nMvLi3dPs1Biv2ZV1yGG+xx20+++TET9lXCbwRPiqBChz5ZUSAtmuW54S0b4ndO5nEzCDFhCgCzEUbbh+IRcEEIH7fnC9n8Enr0TnzJuQaF3G778jq12vG2IEBI6VgJv/z5g1IGv3QgUGI0fj6j4xzefi9+7ehW+teME3vaVsFZaiBAufAjAHZTSL1FK91JKbwdwCsAH/TamlM5RSsf4PwArAawA8CWfzSfEbSltLZaIgEIRQv24oaFQHUaiE6MD19rbmpRCUwjymRy2rewAYsyQzBQPWfuy34z1fVms68sA1QJQnrb2lY9rmIwh8mPBxN6BKFjdnUYhv0E+NwHmACtG7A+70C43lKnoVAQ4F0KhakoI3FYPMXVoxAmF4o5OR4r9na8wAznmN6MuHIc7uYX8BrvItnuMml4CUZmRVXNNgHWkY6hkl7vaV+1+yY4WwcjAdZKTJM+uUwyM3IXs/P5Fw1wJNYQwVtFmWMyxc4zFhI+tYUr5bKw9gmCHnYMTB5qieOrXSUa01edUXLOXmyYNVHGc7ji/6XEBIGY74f6wQ2WJ6slV5NBUgkREMKS71wFdazHec6W0XSYeAbIDAW2w4yiE+AqzAIBpOmISDrNI7Gdauu7UZCGO1skhBOjJtqLoLdfQY3lU3us3OnAd5rNrkIn7C87wYzadzBGey5WCw+p+hkSHsZR2PS8+aHb/r+7No52zly4lXEKNpoqgbvBn0aM+qhAUa0JB6xbDiE3qhP4KvUIxs1LezpU3zPPWWKFq+R2z2LsgdNCeD+z9Ieg9f47/xsX4SfZN+Nq7LkQ2fvqef4jfIHSvA972n0B1Dvj6DcAcMy4UheBDr1yLf7hlC548XsDrPvcLSQI2RIjfVBBCogDOB3C3a9XdAC5psZn3AniWUrrdZ90OQsgpQsh9hJCrTqdvVAhlcUL0qMcYoJTlZ12wopOFOnp+sAkqiT5EVAWaogBHHpSOIsI0TVSSfbYB18zwJiCekKelHcFKhEE5aIYloc9tIEpFx1Sc6ZdhO2hQJIXDSqIXmlGGWjhi78PPH0+BqlohgZpRgSaEUHHWgo+Lh1dV410201OLd3ryuvzO0uaBPDrSMV+jn28vGleUKFb4o7PMX+AFbJuEu9i4sJp6nfugfooQQ0ojKkFHKop6VDiOu4abxaAFu98Mdq0yVbFqVbnG7eohk123HLRoyuOAA8CStiSq8R4P61dKLwNyXtVDP4dTPL5vWQveK/eJ69kA9G5CJCqHpykEQP+5wOAFcEOzqB5C4JvzRUCgm46abIWNfgAAIABJREFUJ7/2LLeMYGTgeleoncWg8TwuQtDRinAJIdJ1jNWmkKyMWqHPrk2pKQlyqIZcY5WgeXCfpDwqXWaXw+N+DhaB2CcKYE1PxlHYJIoTeODqW6w2BdNg536ghfJU9WjO0z+A3Zm2o8UukLR+9dqNvu35OYeGEsV8To58NxXNrrMnHl835RDH1d3pRUmb0EE70xh9Eub3bsVurMIno7+Pr9+6jb3oQ4RYDP1bmHDIwhTwL9cB04fsVTedO4B/f99FKFZ13PTPv8B9e8fPYkdDhHhRoBOACsD9MIwDCC4+ZIEQkgPwJnjZM87AvR7AzQD2A7gvKLeNEPI+QsgOQsiOaoUp9lGTCuFXwvvfxUA4P/pOOOTKzjSS1g83JSoWUkscE0IMr3IZDA2TwlSijgHkOzsriIS4Vg+2p7yb2xsST5hYPZKDaVJmvBE+Hio4hkRuQsCGgXYrb80JcZzqvMherxJRWc0KEXWNJ1k+iZ7xB22VSNWoshpR1FWLi2gwtCTGeq/EfFaW7PdrV+wvr3vkt71bM2OzS2DFI8rAoWi+TovcZ36NLMdgUTdKDC21cqUIQSOSsdVE3WIrAIFJqe1MuHN1AACrX2F/5Mys6PiLaoV2q4rjqNJYDnOd53q2YfeM93iUqEDcK1Tjdyf35RKAHQoanL8VVKfr5et7cd5Sl6McibPr48JUqWH1g6Aa6/QegzCjv9C2EdPLXi1cN9hqoCKTwwWDRAY6FWsucsIhjiZitbm0I4kel4NXzCyHkV3iCMhI+ZWsJe54VXyuo3iPyk6Oa4JDdLiCCrbDX1pFVQiy8YjNjksTQT5ON3doW7GpKYn4T5J4VFRdDlzSe30BoFTTUanLzrnhU1ScElVyQrnzbJiONL9JNOQSi1/v0EE7k5g7Cf2bt2Bcz+APlY/gK+99WUuefogQNpZcCLzjh0C9BHz1OmB8j73q/KF2fP93L8VQRxLv+doOfOru/U0T5kOECNEUbwX7DfyGuJBSup9S+gVK6U5K6SOU0tsA3AXgw36NUEq/SCndSindms+mkFo4btUT4iF6zg+xO/FdlDoHAOg1tKWitoJhI8KMK79QJPeTzwrlKoIx5WcAW8sJcN5QO7qEvBseshf1qPWxMDi3cIKhJTFTrkMRhAtMKoxFzAdzCaZ0ZhNY0ZVi2/J6XJrDthDizJ9TwdgV0Z6KYkVnGp1Wv0rpZb4hQ9xIM7SUx0EGmsiEA14JOGsUbD95x1RMbnugLYX1vVkQt7qgGvWEOjW0NGbbzhGWyNeQEGB2QWZAAKCQ95/tn6s0+J6C4IxLcMRSbyylhzDZdTFmei+V2qhH24B4DnnLkOQsEpfSLycHUIs7xqx9nYTzcv/+CRR0ryGqEQXXbuyFx9gPKuZuXSQxLHdNT9pmbCKRSLDiZcBiRdVcNbkIX+HZlte/IgQoZlfLzCRkm9+k8j3DH3HNlXBFiMPkKAASUa0Fe9EV4ig48PxW5dFaVIlCH7jADjusJPrQu/Yi9GSZU9GViTrsTsSPPfd30DwWh7Dg4pXO/UBAPE6jG+1J773BQyZFNi4TY+fGzrNNO87m6m5v30/1XQMQgvGeKzzrFCLmyllMsriBOzHOAiUKChV58sdUZUdxtm2TdQzWRkRVoKnsnWwKNSsL+Y3AhtcxobgmCB20M4XyDGpffwOq5SJuV/4Mn731VVjZ1SRkJESIIPRvAd71U2a83HE9cHKnvWqwLYnvfuASvPH8QXz2Zwfx7jseR6Ec5qWF+I3EFAADgHv6twfAWAv7vxfA9yilzRNdGB4D4KVfXFAIQaw2YxlJnAVR7fwft4NmT1JzA8j6wbbDFJUo3EaZva/ru25SlDLLoRASqK7H9mPuUmc6bqsvAsxgBYDhviz6c87+pqKx/hluZooZsuVEn+NMNWOGtLgjMEEUqISxedOdW1FJ9MFQ4yAAlnKlSF6nlijYPJj3nIMVnWm0p6IYtLbnRhdXK4xpKmMNhP2YoyuEIZKIK5RKdgYvXeUSCelcbbOeblZBDGviY0zGNOQyzA7oTMewpjsDaHG4r15EVYSZfIeF3LK0nZ06hdi5YKX0cowMvto6N82ZDWbk8ll7VVjnONRUiaAe64BBicSi9eXZ5MCKrhTOGcxDIQSTXRfb4it+7MTmwTxIk3BDDkVh18fXqfJx0vy5YGI/QJlk8P0emOfjDscjAcvh3OuEANtWdaJ73aWoxdrtkEbx3qwbTv8JIbYTpikEW4fa/ceksOP69bWQ32Afh7NxHHwiRxEYZ3GigIBgIT2EkcFXw1SjiLcPYklbEluH2pFLRAV2kXjELUTOVo5kDZ7R4M4fwK4xz78Kgt97jfeeKAqGe7MY7s1ibW8WfbkE1vZk0J2JQVVV2/HUfCZRTB7urEZZSCtgKatabLSgMiqPFFCE52S6wwl3rUW9apzukM5yaikAYvt4/H2oEiKzlARsImCoeSR+6KCdCVTnUP3qTcD0QXxY+SP8zfveiPUtqAaFCBGI7mHg3Xexeml3vBrY+0N7VTyi4m/fsBl/87qN2H5oCq/9p4exe8RfJjlEiJcqKKV1ADsBvMK16hVgao6BIIRcCOAc+IuD+GELWOjjotg61G4lugtKhHym1V0Dy2bQrOVWbhIBkzDvzydwzfpFozUBACMD14EqEZiZfssYF80OgZEh3OGTDRNuLEVVBbFlzDBJRLj4AmEiRgK4kSOKz00Ua47RIhpfBEDXMKrJPuu7Ck1VQKGgEc1jYPNVyCXZOeO7OcajgmjXKslY6csJhqAdSqoBq19h5zXlExGUE/24bmMfbtwygFdt6MXFKxwjq5wcRGXZNS5LWa7tlIqLSowE0OI266kqxFbJu3bTgFechYdCWo5vIqIim4gAkYTHCSlrOUfGnlLbIjbhzMS7m1/XJ9sYXmfHEgCx+utVnCNSTbm6kpDuh6WWMISS7raOT5gKpeWg5dNyyQWAIKoqLMSxab/kfUSYSgTwy/HyY4UJQGCAgCAr9KU3K7M2gQxpUC6ij4NWi7Xb/ejOxNHT1YWprm2IWKUcgpzAgCPYbdl9BPE9LgAspJdJfVaEXLJlHUms7k4jqinoysTQmYpKrJWnW7E00LvZ/irW7eJjBJi6bESQ/ZfDRN0hgv5Y1pGSjs+dtUXzrvjklBpDOqZJpQIy8QiWtqcAgUFbTKoe3eswMvhqqbzG6j7rPUsNUEKkPonXpX+JU4B+IT3kEUHxy7mjhKDS4LXTnHcFFUKegwSZ3AgdtF8XtRIqd9wMbXI3/kT9I/x/H3gf1vY2l84MEaIltC0D3nMvmwH61tuYMqgQAvSWi4bw7fdvQ0OnuPnz2/GNR46G9dJC/KbhUwDeSQi5lRCyjhDyGQD9AL4AAISQrxNCvu6z3/sAPEcpvd+9ghDyB4SQmwghqwkhGwghnwRwE4B/arVTTNRAlIrnbIObQXOFOFrGgaIwFbKYpiCi+hs0Ykv1aJvdBiGWOSW8Cxz2hMhMjZhnIjAfRNEw1ns1pvuvsraEx0HTdCbCEakXHEfTOoYvxNAsRZYBX96ZYjL6luiItDkhwMB5MDodAlOcmeeb5RNRIJ7Dy9Yvwcb+HAbbEnjZcG+gYVhO9qO3oy0oVQ8AoMQy6LLyXYxIEohl7NOqEII1PWmWmxfLeIx0ao+DC6JYUCKeHLTZ/AYUCXOIqolurO7JYGN/DplYBB2pKJZ3pjyiCUvaHKfET8BFtVgZvpepRLC6O43hXsuxI3KBakOJ4MTA9TZbY98Pyy5zxkQ0WxETrlwd7jgQwxvRITK17NCsV31p55qU0svRuXQ9YDIHTQy1tUVo3IIPpg5CgCVdbejNJbB5MG9fb+5wLKaU54UPW80ZNOt7OqZheWcKNSsfjfdPUouExWK65mDEdfY4CAEULZic8gvFBKsjxnOZNEXBss40NJ+C4tLIutYAG18PwGHgxDGy5Sq2LHUmMxRFUF51O2gBJkebK3xxqCOF4d4cujNxLFl/EWOTOfrPtfMd+VDNJlEA6Fxjf3Q7aAupIf997Pcj0Ndm3ePUwHBvzlXf0WlvsM3pAyUq5vLrpSZllVUHDdOt1ui6d1sQUwFCB+3XQ6OC0tfeiOjYE/io+of43Q/8LlZ1h85ZiDOIdBfwzh8B628A7v4o8OMPAbrzA3ju0jb8+PcuwyUrO/Cx7z+L2/71CbtQaYgQL3VQSr8F4A8AfBTAUwAuA3A9pfSYtclS658NQkgGwG8B+HJAs1EAfwfgGQAPWW2+mlJ6Z6v9SsU022i+bFUnMom4tVw2WjwiIQCw6uWorLgWeiTNjDEf0QTAcVKq8W5MdjuhMoqqQNNLyJQOOxsLxhdVIoztMRroTIs5aIKxQRQYWgJGVAjTtwRKuOHciDCVNE1fkJgYP5U7dmCxXhnDhsE2XD3cbYWCucKq3AyHpGhIpO3W9mSwzcp/ySUiiEeYHH7cpdQnBzCyPCb4bGGH+qmaXeNttvtiQFGhW3KJqsKM4kT7IKDFAo1rxzATLHV3GB9RoUcyGBm4FpXkANJxNgZFUbC8M414rhtursJ7PHlBPKJaDBrPQYsAy68QGAmZQeP7gLCC5XaooqICmV6rDRWV5ADGeq8ETcuiE1wl0HsaCBIRxc4VBBynacvwGqj5Qcy0bcGWC6/A5mXOONf1ZW3JdaekgXjdmbNACKBqMazsTDMGz1o/n10jHSsI8Txjde1TofkIUAjGPftLsHkwj1Jadga60t6wTzuK2frbk/XJyyLsuME9FRnwgE0GzmMRN1ocl67qZM+VuxVRfEaNSHXSdI05KZWExXILjCuJZzGb3+zsK0G+h0SWiW/ZlY5BIQTprbcAm96Anp4BxiZzdKxkfYfj7BpqzF/tNJa1+uCUKBBRjfuLfNh9Ik44N6EGerJxyakVy2fw5yMRUaUabZsGctIARbGQ7gxXk3XOn19x7FYQOmi/KioFzH3pBiRHHsHHtdvx/g9+KMw5C/H8IJIA3nAHcOnvAzv+hYmHFI7bqzvSMfzLOy7An143jHv2jOPVn30IT50onL3+hgjxAoJS+jlK6TJKaYxSej6l9EFh3ZWU0itd2xcppWlK6d8GtPe3lNLVlNIEpbSdUno5pfQnp98xZhh3pGOIGBUAQLQ+jRu3OLWWTL/p9UQeJCrM6Kqar/T3QFtSMno53HlugMOgEWrCVCLMuTMaWCLMHCtCaJppOSG2MIjgVHAGZi43jHokh8jQxSh1bLZnrlO6t3CuJ/xPtaTz052s/hS4geyrAenpn3tdJh7xETeBZ6ba6/TJvNTKrjQ29ufYdilX/pm1ZZ2ycxnhx+vwT00kJptIIxoz2GwHQFF986zYxqztKC8fUJkBNtwMrLgSBdfsfTO/Y9VgLxIac7a400sJgFS3nZMDonichVXdaazrzWLLkjb53C25GFh1DXrbMkhFNRhaKjC0zH2OKc+hlEL6LKgaqn0XoZIacNprWw5k+xFRFQy1M3XCrgDVvvncWtTiPUBCmMTgPoh1jpuSFZvegIWuc61+WhcolgZWXOU/Ntedx4u4cyfQXYTcMKknqoXngInspcI76jqlnHnnTwX19MBCpg9oX8FYqHWvQWc6hkw84q9QGgSiYmTw1Uw1lkBy0JQ1r4KhCbXdBERcz91cfj1m2zbbmy6klviEQQptRGSmTO9cB4Aw0aBV19iOm6cF4byu789iTX8H6tG8VJDdDwohUKz3D6jpeZCoGsd8ZjXmcutsB7Y3G5fG6VY8He+5HGO9V7L2+XtKmBRz5742D/sV+trSViFkFMcw/4VXIjG+E/9/8kN4/+1/6tRxCBHi+YCiAK/4K+CNdwCT+4EvXA7sv0tYTfD+K1biW+/fBkqBN35hO7780OEw5DFEiLOETf0ZW8Zb0RfY3zrLWVnewX4vIvzH3JRZJ7GArfzBQURlIU1uEB/DuZpgCeqmogGRpGVQuhkZZ7+OTBxbluSxsT+Hq4e7cf5Quw/royCx7pXYtGET6tnltgMR73AIy+jaV6AnE7dEUwR2LJpkxlefI8EeUVmfuJHbdNaZfxTC73w9FreD5t1CQiKqMhZpyUXAiiusfSzezbpWufVXAwBimgJE03Y+TDyiYvNg3p6oNS15c9NtYFITQZk7a3oyaEtGnWtRnWPvfkLQmXHX7ZKNPvFzIplBPKoCIEisuhwLqaUwVMsZ714HbHoDoCjoTMeklAxNIcgrFas5gVFVNSDRhguXt2Oog7Xjvj6NKGvH7GVqlPlklIWtWn2VthYuy3lDeZy7pM121JHI2+IJqqJgSXvSyUvKLZFGW4t3odB9AXP4CedH2d9arAMLqaWBMvv20CzDW/qpTPkb+e5bUo+kMdr/SugJtr1bqTEvhPlV8yuZgqcFUYBZUQiQ6ZX6Wkovw6l+V3otYXL9EYXIznWAF+pmSKlPKPK63izOE8RLbKgOw6UQSLlgupa2nTA/RrCcWgJsegPqPecy5U23HSI+qy5nmGb6MDJ4PdSIdb8v3SbvW5uXmwKQjGhQ1r0Gk92XSrle21YGOGuW86lQw/uOiCVRzK1BKbMCiaiKrUPt6EjHoAgOGnV9oEqUqcQCODVfQ1c6JjlhYogo4J+75tvNlrYKYYNOH8b8566BWjiK/93+l/id2//UqscRIsQLgA2vA97/AJBfAvz7LcBPPwLUnMLV5w+xkMer1nbjr3+8F+/52g5MFr3yzCFChHh+0ZbQbIaKWCE13CjrSMewvDOF1VsuA3o3yQwAHCW4mJ1rFWxk6ilZqtmPQZvLrcNY71Voz2Vx5bZtQM9GoGOVvJFQY40QBUMdKSgKYeyUpjq5QUL+VyYegaIQrO5JA0TByMC1qHYy6fdERMXm1cuxZOV65nC4QxwTbZKM/fq+LJZ3pJAXjHoRokNgm/sZQUDF10FzM2YOG7FlSd5aJrbrs59lqPJFS/v7sXWoHaqiAL0bpW2Xd6bQnWWGZWJwI7DiKpiW42IP39CBWAZre7zpEOv6snjZmi6HvRDC7dYt6cPmwbydA+YJ3SME9WgbptvPA7HqbF2+tgebVy9DoW0T66fPKRLbkdoMmOXn+Yaiet62lR0YvuCVwNCloO3svjKtIuwAu3b8cyG/AeZKx/GIaSqWdrgFR2SkYhqWrNiAq9f1+azllJkifgOIgkLbJmhxYfJ84HzP3hsHcuhKx+SQuyB4TjkXf7DGKWxw4XImFsSve6VjI7D2enu9IeQpkXWvAbQY6mtfg0qC3dM8hFgcGwAo616LzYN5LOnyL0IuoqbLkyp+VXlSMQ25nNOWYjG/0GKY7tiKya5LQAiRnM3x3iuYEwbvfSieRyO3HH6lLWT1EPna92TjWNmVdsIIY0GRaU4+PgAoqsNsc7aLlxzgKOQ3oDpwCaBZobNmw1v3TvMvDSCK3ywmTDLUkfLUhJNr9YUO2hlH/eADWPjcVdDLBfzj4Kfw4dtuQy7ZwkMdIsSZRMdKJh5y4fuAx74AfH4bcPA+e3U+GcX/fdv5+IvXrsfDB6dw7T88iHv2hIWtQ4R4QSEY151p9qNPVrzMXtaRiiGZSgNdaz27ciW6Hq5WKBo0q17ufN74elx24VZcv8kxXP0cNBACQ0uyGXVFYSqxbjn0RDODj0gM2nlL27C2N4MVVuRIRFXwms39WNWTs5fZjo99nOD8MgDQVAX9ubizrnu9VMcoJggwEPd5CIJHqc/5nk94CxI7Npiwn8LDQ/1YL+84ujNxvHxdDwbb00CqA7kMOx+2/LmpA0OXIjN8tUc8w4bF3knFgvMDiK55uSXl7T3yeUvbMNl9CarJPihVFmYaWWDvfbtelq+D5nx2M0B+0A1HmW59XxaXrOxEdyaOjnwWyPY5HaOWk2axonyxoSagJPzD1iSse630tScbk3KFPGOyhXbYn45UDK/a0Os4kt3rgPblnsPEIxE2GeE6OUO93UhEVP9aaS5wtU0xxNG38LfwzOmCt0SsMD81ErMN+YtWtNvspsO4ECASB9nwOqBvi9NugDPdm41jSXvSZjJlBs36nOkF2oYs1UViF7ZGpg+5niHUY+y9kBBEdsTcVfcpednqLrxqQ6/ULc+T04RBSsU0bBzILSrRb7cazQA9G516cwrBZas7sbwzJUxwMSykl4Gme4AIcwoVs+Z10AL6popOMiFIRFT4l4+32F5xe8iF680mBb1FhA5aK6AUpQc+C/WbN2GskcT3z/sq/vg9b1lULjREiOcNkThw/d8B77oLUGPAN28G7nw/MM+UwAkheOely/Gj2y9DTzaO9359Bz7y3WfsgpshQoR4HhBJOkZg2ql705bUsGVJHm15n6R3H3SkY7hxy4AzA8xnddWIK9+GQLNmjC9a3oFV3WnbcBVlpTn0ZoXtFRWIWft4akTJVphCCIZ7s7JBqhBs6M/ZRr69JmmFGSUCakBJsPq37HKgZ72rgC6rNVaNdaG67nUe1tEXfrWuOKtDnEX2GHw6RtPM2FT86nsFGMaiOl5X71Kcs2rIVtsDNZjznukJVny2DEiP5HzSOYfufKfubAwbB3JQFaGeWScXyvA/DBuCs1KqKRUwtjYrLzGfjGB1T0Yqdi7uRgWVUPG8cnZvUfiJdQDY0J/F+r6sT66iZRgnOjDTfi4U4oieNIXqP8netfUmbOjPydUiApqayW9GMbMSWsbJW+TXx1H9tBpYdwOw7rUYGbgOc7n1rFafBU1R7NC4bExFR4qdAy7Lbj+9qsaiaPikSpBToRCct7TNR2xF6FiKHf+cJXms6EyhEc1jYfmrgLYhXLis3Z78WdHJCq9fsKwd5yxxnj1NIRjveRnGe15mH9NtGzfNQft10bkG6B623zv9+QSy8YhUO1Fysi2BlPZUFNH2pV4HLQDuia/ubMxxZsXtfArD68lOOcSxhVqBANBaz36TUV/A3LdvQ+7gf+Fu8wIYN3wO79q6ZvH9QoR4ITC0DfjAw8CDfwf84jPAnu8D225jgiLxHNb0ZPBfv3Mp/uHeA/jCA4ew/fAU/v6NW3Dhcp+Y8xAhQvx60GIsjKpjlZzcTikzfn1qUbUE3lbXusBNenNx9ObimD3IvlcS/Yg09kvbLJqTGmQ4tGjEiLBtotwSJrgRSSAbn8B8tYnKLK8X56cEaeXfAMFMhncft0iIcCg/Fo8vEsZr9J2L8UIbEhE/h6G1fkQ6VwCnnmZfkoJ8OSEekQXp+GaAIqaFerQd2XgEWy84H9BUrOxKsxy4XVa/ssy4VgmB4RFId/pg91Ml7FotTAYecyCfQMeG3sAJ6lRUQyKiYkN/Ds+cZPU5VUUBCDNcFbOxqM/UDFwpe8GabHQcTHZvGx2rUKEJ+GRn+je4SGdIwGeAiehMlWpoy+dwzBhGR9pbn4+63RONC+8oKGWWo5RxWD1WC497uE5NwECDPjsAVGYDnUyODf05tKeiMvPFQ5p99qWWIIiiEDsvTomlkIxpQH4AVFQ9jCSgm6epXt5iDlbTJuySQ+x7TFPxqg29HtYMYE6jacjXYcXlv82es7njnu39oLqe067zbsS10TR+8PSoq1/smRUdsvLAZTCPH7C/y+GOwQgdtGY4uROl/3g3MsVj+Lz227jsPZ/ApiWtzYCGCPGCIRIHrvkYcO5bgZ//DfDQ3wM7vgpccjuw9V2IJtrwx9cO4+rhbnzo20/jTf/3Efz2RUvxkWuH7dCHECFCnEF4lMe4WqPL0GrVUlUjTM1PWdywcWpGKVjWlcfBGacsh254HbSrh7sdI52H4Zgupl1p/T1hy4oT4YMVwrVtZQcK5YaH/bExuBUY220rKF413C0oQBJ7bK0b+O4QRwe8D7LT5qpLBzZzrkcy/op4LXfE2i7TC3QNS2t82SRukLcta9rq1eesRFRb7aXIllwElKed5hQCGP6hpeKuqkKAbL/loAWPrVn0kKoQvNIKcdMNFmoZ0xSUhfJokRbuYw9irsLc1l+7l5YzS7jxy1fUmUAPasXTPybkyQD3tbpweTvKNQPZhIbh3ox0XvgEgCPUuvi9koxqOGcwj2ylKA3BLmzsboMXrVb92Ua7LwrBYFtAnp/AVK7sSmN6oe6/bTTJ2D8tiog1qFN91wBrlgK7Jnyb5t2ttK0F+ru9K84EhLaC7stLVnbggQOuSQfbUWb7rOxKY6Qa83XwAK+DhljG9wm5YCgPTLFrZioxIMrKpVQS/WCVYCyxphYQOmh+MBrQ7/9bkIf+HnM0j79r/yR+513vQrdf/YoQIV4saF8OvP7LwLbfBe77K+C+v2TM2rlvBS76ALYuW4m7/uByfPqeA/jKw0dw755x/OUNG3Dtxt7Tk+MNESLE6WHoUmDqAAtNknAaz12LRi2fWaZEQWzzTRjf5xhPfhGOGTGRPtPLjHN3eNlpMGi2QeoztnhERW+uSXiPFgMGHSEHKclfr4AAaESzrZ8135l6t9MmhGnCCNzP15FqlQng+0aSPuGiAfusv9H3vK/pyWC6xLydRDTgXOaXsH8WNDvcznsDyAyaElx5+FfAhcvbcfB4GQldxYyZw6y6Gtne1cEOehCWXW6rZXJQF4Pi1HvzhrUBaO6gdQ175N5tiFGBrlURVUEu6V8I3f24Bo1YLLsBWMqPVQJQ6rBwlsOuuid4eF5oK+G+QRBEMRJRFVescZeXELdlTg23FxKJNKBGcOkq/9pjfLtKfi3QIUTtnC6DtvwKoF5k4ZguxrQV2yWfjKIvl8CpuYo3t81S1kznOrF2a3BeazSWBFDxXacqTtH39q5eYC6J+dwQGtE8sHYAZGROfu5bzEELHTQ3Rp9E9b9+H/GJp/E94zIcv/Av8NHrz/cPQwgR4sWI/i3A2+4ExnYBj36esWm//CIwdBmS59yC/3XNjbjhnAH8yZ3P4IP/+gResb4Hf/6a9VJNpBAhQpxBZHplxUGO52FixLF9CUAIiKLYxqxbdtuDrrWMQYm5QpZEx7JtOTOWguChNs4QTB2OcTrNAAAgAElEQVSEWEVhxbbjeaBe8t/HZQhGVAULqUHEq+N2AXDpEtgJQ2JNOLbM36c43UF6zz93kD3RDAFha+v6sr7Lm4E7RKZP+TVJUE+0c87AvdmRjqFjeTtwkEAhBOXUUuR+FfYs3e3pj4eptZZUGuyvLcDSNQxM7gOWXhzcfu/GwFXiUet6QP06Hzghju5+MlyyshOVuk8Ia8cqYO4kkBsAsaOB2TnbMuRi5rvXs/vY793SKlRvLcVWcNVwN+IaczQ6A+rUcfzaOWjpLgBBjmNrbWXiGk7N+Txn3DE36t6dACbzX5lFJOo/xktXdSIV1XD3njHWGy0GDF+PxlMjnm2nuy6E1uzd6ULooHFUZkHv+2tgx1dQpFl8TPkQrnvLB/D64Z7F9w0R4sWI3k3ATZ8Drvlz4IlvAM/8B/CD24GffBibVr0cP7j0Wvzr7DA+8cAkrvnUA3jXpctw25WrwrDHECFeMDx/zDUlTNr8+o29WKgZuP/ARHOREA63cwbITE7X2ibS107OzRkfmWkAIKBEk0melVc1KfwsOwPxiAolN4ha15At7x238qUG2xLA4V3Wfs4MNz9lvgxa9Nevf7qkLYHIUPvzWq6HM2jGIgwac+TOcO1MK5+J5pYA5RbyIKV9Y4Be83UWPUxtx2pgYQq93d04pVdY6QeAOV9NHLDmx49LDE27T2H4IPB8SR4yl3QpdrrFVWzEs8D6GwAARGcemqoxkSGPca/FfJUpTwsBYiyLwS1h74fAd8CZmJg6TaZ3bU8Gg20JqZ4bAOcZDgonzg0AuQEEcV7cOb1quBuzC46T9/J1PfY9wJ+xRqIb1VgThtKF0EEzGsCT34T5s78GyjP4mv5KPLrsg/irN23zLcAXIsT/OGR6gSs+DLzsj4CRncAz3wL2/gjqvh/h7SD4rcHz8EBjPb720CCu/eUGvPuqDXjLxUs9PyghQoR4kWDoEiYO4AOFOIYLAZOvT3HtjV81fC0isOuLhCfZ4U9nWuXYNKAQJlEtMYGKCgSZTz6G4NXD3R7DcVW3ZcxzR09UXHOH0gGs0LOh+4SsBiBQb5ydr+e7lup5S9twYLyINp+yQNx4tKOE6BmmQCNxYP2NoHMN4Pjs6bl/K68JvM8jlmpfno8pNwBsegPiALatPEPRIGuvx7gxBugUV6zpakH6nZ3P/8feece5UV2L/3ulrfYW9w7YFFNNMSb0hBBMgJBQkkB6eLyQlxCSlwepP/ISXnpeXkIICQHSKCGQBBJ6L6bYBmMb97Jua6+39yat2tzfH3ckjbSSVtrVrqTd8/0g5J25M3POzGjmnnvKtRwFPuZNKeeMw6czK5lBloJIZKxLxVbYzCZDFBgZCZHbPv6iqyQ5dRngK5vBJG9DgnzfxITndBy8wp12fu/ZR86gOFCd0CiuKiuOMVqdlVzDaprBhPR/ARO3B2ZZsO1R9Ms/RHXsYYM+mu+HbuKKSy7hzjMPk5wcYfyhlEnCX7AMLv5faNoEO5+hZNcLLG//K8tLQgR1EetfPIK/vLKEuce/m/POfz+V00YQPiEIQnKG+56pmmc+CXDZniHnvF1FSSZuTRtngYYhDLTq8mKWHjo1+wOcVtC8l5U7/cHzBLKmnGQ23N5RNS98qEFVH9M1zmLIsncqTSaXFnHKoYkLnIVPxyCDOpt9IHcxLtcwpngpmTRoIuMwk0qKOPeomaMb8eFyodxuCAbTrhx67NxKtjb0xBRCGe5vIXzEUPFkoAOmHDas/SRkxlHGOzkGDB4YUnHfmeOZfAgDZbNHln8XJs44e//xcxJ6zGdUlMJpV2e++xTzEKZi4hlooSBsfwze+BU0bWK/+zB+4L8J/+EXcuvlS1g0Y+QhC4KQ9ygFc08yn/O+ZRKoD7xJUe3rHL9zBcva/olry8OwBdpL5lF0yDKqjzzDlBCfc2LSl6YgCBmQhXLTg5h5DD1VnXgmzYvpELz/+DmpjZNUFDlCu9LoZYxKPuu0Rah9e/CXVA+dSxcm0/O78GyT/+MoGDGzopTDZ1REQ+aGQ3i+qrhCF/lA+EyWFrvilmSXcP5WNuePzSTkcLioDG2JI2dVRqYCGCnhK+GrXAhz5sCUQ7OyX8C8+0eZpEZteM7FWceNaP/WMPPnhiLbcxwPd6xj4hho/n7Y+CCsuh06a2kuPoSf+b/Ayknnc/PVS/jgiXPFayZMXEor4ajlcNRyJi8HfL3s27SSbWtfwd34DifsXkX1nscB0MqNmnUczD/FPOTnnASzjxejTRAyZRTCi9xFRfRWHQnEdpBG1OlwdoRGw6hMh+oFdB5xGVanJwMPWobv9NJKmBU715zLpViyIL0wqqSUTzVVGeOv98Jzk1cPHCPChtPkQSHt2e0PzZtSRmN3KUfPzo7xMlakPefeKBBJrXQpmJpF79kYkTSyVylY/P6xFidnhAeUAqH0i8zAeDfQtIb69fDOfbD5EfD3UjfpOH4SvJEVodP49/OO4MV3H544LlUQJjKllSw67SIWnXYR3Z4AD68/yCvrNlPavIGTXXs4t/MAx7Q/Rtn6+0x75TLVp+acCHNPNN9zToTJ01MfRxAmMhnML5b2Lh1GybA9ZvE4DbRRzFkZinCCf7K5ivKaROetMvdFyOZNKafT4+eYOXYYa4ntKUxULGYElBa5OeuIxOXY85rYqu5jSpGdZzd9DDyFo0Hk1OUmsjdvGAjEGmZJ56SLY/wZaFpD8xbY/gRsexxat2O5y1gz+Tx+2X8G73Qv5iOnHsqKC46Sec0EIQ2qJxXz7+cs4t/PWcTe1vN5YmMjN29rYmtDN/No58zJ9Zxf3cQStZ85tasp2fJwdOOq+XFG2xITpiHeakEYHQ+awyhLp6hBWoRzskYYkjRSFs+uYMqk4qHf3QvPlWdMmrhdihMXOPJ4phxiisLI4BrgtM/G3sqYXFrEeYtnUVk2/rrqE4mQPb9FODc3XOBmKMbHVe+uh/2r4MAq2PMydNaiUbRMXcrDk7/Ene2noINVfOLsQ7nt7IWjXjFJEMYrh8+s4D8vOIr/vOAoWnoGWFHTyhu72vhRbQcN3QMAzC/18oGZrZxeXs/R1DKrdSfFu55DheM1yqYYQ23uSeZ7zokwY/Ewk+4FoQBxFYEVzGgC6Jyz5CO5lgClVHoFF/LAM1XQiHEWIZz6ks4MFaNBdYLKmwVDJMRxYrvQwpGNbpfKaNAs/98OWkPtGxDwmMko/f3gaYeOfdCxF9r3QG8DAFZJBU3Vp/D89Cu4q/loGhurOGZOJTd+8BCuXLpA5ncShCwyq6qMq5YdwlXLDgGgvsvL2toO1uzrYPXBOdyzdyH+0JkATC8J8v4ZHZxV0cBxqpa5nhrK3v4DKmiMOorKzOj8nCW2t+0kmH1cVuYZEoS846gLTflw8fIIQl5TlK0w4QmIIlkS2sQiaHvQMr2X8t9AUwruvwKsQMxiPWkGgeqFtE49jc3VC3my+3CeaZtOqMfFgqnlXHT6bK48ZQEnzK+S4h+CMAbMn1LO/JPnc9nJ8wGTfL6rpZet9T1saehma8NM/rVvLt7AyQCUuzXvmdHNuysaOLHoAIf4dlG57TFc6+81O5S8NmG8kqJ8eDaoKiuWeTwFIQssPXQqe1r7Es4hJ6THBLfPIlNYlBZlVqgprw20kKXp8vjpuvgBmjxQ73FR16fY0eliXXOIjn1m1u6yYhenHjaVr548nfcdO5tj51aKUSYIOaakyMXx86o5fl41V2G8bCFLs7e1j22NPebT0MMvGmbR3n8ccBGgObW6n/OnNHFqSR2LQnuZvn81Rc68tsq5xnCbcRRMP8r+PgKqFsSWAxeECcp7j8m/cu6CUIiUl7g5Yf4Iq3hOUErs+RedkzZPRJbMr2ZOdVnG4apq8ARyyVm2bJleu3ZtprLF8M6BTh5cc4BgSOMPWQRDmqBlEQhpAiGLPl+QLk+ALo+fXl9wUPWXyrIiFk6fzHFzqzhuXhUnzK9iyfwp2UuGFgRhTNFa09rrY2tjD9tto21bYw/72vojv/8FZV7eP62F0yfVcxR1zPbXUd6zFzXQ5diTgso5UL3A/hxif+ZDxWyYPNPMQ5TjstYTDaXUOq31slzLMRZk4x0pCIIwXmjqHmBmZWn2Ksra9PmCeHzBgi/2l+r9OOZmbWuvj9dq2ihyK4rdLordiiKX/e12MW1yCYtmTGZKeTHVk0qYOqmY+VPKWTB1EvOnlksemSCMM5RSzKoqY1ZVGe89Ojry7/EH2dHUGzHa1jfO5a/7D8cbCAFQ5IJTZ1icXtXBMcXNLHC3M8tqo9rfRGnDJtSOp1Eh3+ADllRCxUyYPMt8l1VDaTWUVUFpVfS7tNLkxhWVgLuEAauInoCiO6Do8im6Biy6fJpOr0Wn16LbF2IgCL6QRSBoce05izjjcAnHFARBECYmc6pHx4CqKC2KTLsxXhlz7S48fg4XHj9nrA8rCEKBMamkiKWHTmXpoVMjy0KWpra9P8bT9nhbBb/rmkkgFOtuLy+GIyf7WFzWzSHFvcxQ3UzT3UzRnVSHuqjo6mBS2xZKg32UhvoptTwp5SmzP6mCxywUIdyEcFF0oBiKik2lvsjHbX/sv93FUFRuvHrhT1E5FJc5/h1eXmbKXxfb30VlidcVlUNR6eACFFqbmU+1Bhz/1pb9t479LiqXkFFBEARByAHj2/wUBGFc4XYpjphZwREzK7j0xHmR5SFL09wzQF2Hh7pOL219Ptr7fLT1+Wnp81HjCeANhPD6QwwEQnj8ISytcSmFS5nJfd3KYmaxn9mlPmYV+5hW7Keq2KKqOERFkbb/bTG5yGKyO8SkIsWkYk25G4oIoXQIlxXEZQUptoJgWaaUeuQTiv1bhyDoh6DXVKjtbzP/Dtif4ICpXjsslCmy4jS4MuVDt8PSzwzz+IIgCIIgDJeMctCUUq3A/tETJ+vMANpyLcQoMF71gvGr23jVC8avbqJXdjhMaz1zDI+XM5RSvcDOXMuRZcbj70B0KgxEp8JAdBo+Sd+PGRlohYZSau14TE4fr3rB+NVtvOoF41c30UvIlPF4bkWnwkB0KgxEp8IgH3SS0oeCIAiCIAiCIAh5ghhogiAIgiAIgiAIecJ4N9DuzrUAo8R41QvGr27jVS8Yv7qJXkKmjMdzKzoVBqJTYSA6FQY512lc56AJgiAIgiAIgiAUEuPdgyYIgiAIgiAIglAwiIEmCIIgCIIgCIKQJ4iBJgiCIAiCIAiCkCcUrIGmlLpeKbVPKTWglFqnlDp3iPYlSqnv29v4lFIHlFJfGSt5MyET3ZRS9yildIJP/1jKnA7DuGafUEptUEp5lFJNSqm/KKXmjJW8mTAM3b6klNqulPIqpXYqpT4zVrKmi1Lq3Uqpx5VS9fY9dU0a2yxRSr1q61WvlPquUkqNgbhpk6leSqky+3e2SSkVUEqtGBtJM2cYup2nlHpMKdVo/842KaWuHSNxxw2Z/v5ziVLq20qpt5VSPUqpVqXUE0qpE+LaKKXULUqpBvu3vEIpdXxcm6lKqfuVUt32536l1JSx1WYwtn5aKfUbx7KC1EcpNVcpda99nQaUUtuUUu9xrC8ovZRSbqXUDxy/lX1KqR8qpYocbfJap6GesdmSX43huzSVTkqpYqXUz+x3Q78y74q/KqUOjdtHqVLqdqVUm93ucaXUgrg2h9rPm3673a+VUiVjrVOCtnfZbb6WTzoVpIGmlLoauA34MXAKsAp4Jv6GieMh4CLg88DRwEeBTaMsasYMQ7f/BObGffYCfx99adMnU72UUmcD9wP3AscDlwPHAQ+MicAZMAzdvgj8DPg+RrfvAb9VSn1wbCROmwpgC+Ye8w7VWClVBbwANAOn2dt9HbhxFGUcDhnpBbiBAeA3wFOjKFc2yFS3s4DNwEeAE4DfAXcrpT4xahKOM4b5Psol5wF3YK79+UAQeFEpNc3R5hvATcCXMb/lFuAFpVSlo81fgaWY9+pF9r/vH23hU6GUOgPzjo9/txecPnaHfSWggA8Ax2Lkb3E0KzS9vgl8CfgKcAzmOfUl4NuONvmu01DP2BHLn4N3aSqdJtny/cj+vgw4BHjWaVgDvwI+DHwcOBeoAp5USrnBGOeY92elvf7jmPfOL0ZHpfTehUqpjwDvAhoSrM6tTlrrgvsAbwG/j1u2C/hJkvYXAt3AjFzLnm3dEmx/NqCBs3Ktywiv2deA/XHL/g3oy7UuWdBtFXBr3LJfAG/kWpcUOvYB1wzR5otAD1DuWPYdoB67Ymy+fdLRK679b4AVuZZ7NHRzbPd34JFcy18on5E+s3P9wXRkQsAH7b8V0Ajc7GhTDvQC/2H/faz9njnb0eYce9nROdKjGtgDvBdYAfymwPX5MbAyxfqC0wt4Erg3btm9wJOFqFP8MzZb8pPDd2k67w3MYLkGlth/VwN+4JOONocAFvB++++L7b8PcbT5FGbwsyoXOgGH2ef0WKAW+JpjXc51KjgPmu06PBV4Pm7V85gRwURcDrwN3KiUOqiU2mW7IStGUdSMGaZu8VwHbNVar8qmbCNhmHqtBOYqpT5ohwzMAD4GPD16kmbOMHUrxfyAnXiBdymlirMr4ZhyJvC61to5WvUcMA9YmBOJhOFQBXTmWohCIEvP7FxTiYmmCV/zRcAcHDrZv+nXiOp0JqbT43zPrAT6yZ3edwMPa61fiVteqPpcDryllPqbUqpFmXD/GxxhboWo1xvAe5VSxwAopY7DeHHD7/VC1MlJtuTP93dplf0dfmacChQTq3cdsJ1Ynbbby8M8h+kPnTqq0ibA9v49CPxQa709QZOc61RwBhowAxNy1By3vBnzw0jE4ZgRipMw7sobMG7le0ZHxGEzHN0iKKWqgauA32dftBGRsV5a69UYg+wBzChGK2Z06rOjJ+awGM41ew64Vil1mm18LgM+h3kYzBg1SUefOSQ+D+F1Qp6jlLoUeB95MElngTCiZ3aecBuwAVht/x2WO5VOc4BWbQ8ZA9j/biEHeiulrgOOxHgZ4ik4fWwOB67HpCy8H3OdfooJCYTC1OtnmFC+bUqpALAV41G7w15fiDo5yZb8efsutQelfgE8obU+aC+eg/HCt8U1j9c7Xqc2e7tc6PQ/QJvW+ndJ1udcp6Khm4wLXBh37Ce01t0ASqkbgOeUUrO11vEnuFD5FEbXnOYBZAN7ZO124AcYg2Yu8HPgLiDvCmpkyA8wP95VGKOzGRPm8Q2Mu1wQxhw77/OvwFe01mtyLY8w+iilfokZvDxHax3KtTzDQSl1NCYc8BytdSDX8mQRF7BWax3Oz3pHKXUUxkD7TfLN8pqrMe/vT2CMs5OB25RS+7TWf8ypZMKQ2F6nvwBTgA/lWJxho5Q6D7gGc//lLYXoQQtbp7Pjls8GmpJs0wjUh40zm7BLM58SuYejm5PrMLkjHdkWbIQMR69vA2u01j/XWm/SWj+HGU38dHwVnRyTsW5aa6/W+lpM8u1CzD1Yi4lTbx0tQceAJhKfh/A6IU9RSp0DPAN8N8WIojCYkT6zc4ZS6lZMUvv5Wuu9jlVhuVPp1ATMdFaVs/89i7HX+0yMJ3OrUiqolAoC7wGut//dbrcrFH3CNALb4pZtJ9pnKbTrBGaQ9f+01g9prTdrre8Hfkm0SEgh6uQkW/Ln3bvUERJ4IvA+rXW7Y3UTJpIgPgIoXu94ncIRCGOt03mYQf9GxzPjMOBnSqmwVzDnOhWcgaa19gPrgOVxq5YTG9PrZCUwLy7nbLH9vT+7Eg6fYeoGgFLqXZgQznwLbxyuXpMwHR8n4b/z5r4dyTXTWge01gftkeuPYRKlC9mDtho4VylV5li2HFMdqTYnEglDopR6N8Y4u0Vr/atcy1NIjOT3n0uUUrcRNc52xK3eh+lcLHe0L8NUKQvrtBpTXORMx3ZnApMZe70fBZZgRsPDn7WYys0nAzUUlj5hVmIqTjtZTLTPUmjXCZK/18Pv9ELUyUm25M+rd6mdG/83jHH2Xq11vPGxDggQq/cCTPENp07Hxg2wLwd89vZjyR0YXZzPjAbgVkyIP+SDTqNZOWW0Phg3uR+Tt3MsJja7DzjMXn8fcJ+jfQVQB/wDU9b8bEz5zX/kWpeR6ubY7g9ATa7lz+I1uwbz4/giJhb/bEyhl3W51iULui0GPg0chSnv+hBmlHdhrnWJ06uC6MPLA3zX/veh9vqfAC852ldjXk4PYUq2X4mpRHVTrnUZiV72suPsNg9hOn8nAyfnWpcsXLPzMMnpP8eE3YY/M3OtS6F8hvr959sH+K39uzw/7ppXONp8E1P5+Er7t/wQpgNT6WjzDGaKhjPtz2ZMXko+6LgCu4pjoeqDKa8eAG7G5Nd91NbhS4WqFybv/yBm2oCFwBWYqJFfFIpOaTxjRyw/Y/wuTaUTJhXqUUy1w6XEPjOcVSZ/Z1/bCzDTjbyCyW112+vdtp4v2+svsPd5ey6uU4L2tTiqOOaDTmP+A83iyb/ePqFhS/XdjnUriCuFjRmJet6+UPWYl1TlWMo8irpVYjoE38i17FnW68uYOHUPJtzjAWBBrvUYqW6YTtw7tl7d9sMvJ6Wch9DpPEzuZvznHnv9PUBt3DZLMBWrBuxr9j3yrMT+MPWqTbRNrnUZqW7234na1+ZC/kL9pPr959snyfXWGA9quI0CbrF/wwPAq8AJcfuZislH6bE/fwGm5Fo/W7YVxBpoBakPxpDZaMtcg5k/TDnWF5RemL7KrzBeQC+mAMqPgbJC0SmNZ2xW5GcM36WpdMIY0smeGdc49lGKqRvQjunbPIGj/Lzd5lDMVAseu92vgdJcXKcE7WsZbKDlVCdlH0AQBEEQBEEQBEHIMXmTyyMIgiAIgiAIgjDREQNNEARBEARBEAQhTxADTRAEQRAEQRAEIU8QA00QBEEQBEEQBCFPEANNEARBEARBEAQhTxADTRAEQRAEQRAEIU8QA00QBEEQBEEQBCFPEANNEARBEARBEAQhTxADTRAEQRAEQRAEIU8QA00QBEEQBEEQBCFPEANNEBKglFqhlFqR4TbXKKW0UmqhY9ktSqnzsyyeIAiCIOQEeT8KwugjBpogjC7fA+QFJAiCIAixyPtREJIgBpogCIIgCIIgCEKeIAaaMOFRSn1MKbVDKeVTSm1VSl2RoM1MpdSdSql6u90OpdTnh9ivtv95sx3aoZVSt9jrTlNKPayUOqiU8iqldiqlfqyUKs++hoIgCIKQOfJ+FITcUJRrAQQhlyilLgD+CjwF3ATMBG4DioGddpsq4A2gHLgF2Ae8H/idUqpUa317kt2fCawG7gHuspcdtL8PBTbY63qB44HvAocDH8uSeoIgCIIwLOT9KAi5Qww0YaLzP8AO4DKttQWglNqBeXHstNv8J3AYsERrvcte9qJSagrwPaXU77TWwfgda63fVEoB1Gut34xb90j438o0Wgn0APcppb6ktW7PppKCIAiCkCHyfhSEHCEhjsKERSnlBk4DHg6/fMC8OIBaR9OLgLeAfUqpovAHeA6YDhw3jGNXKaV+ppTaA/iAAHA/oICjhqmSIAiCIIwYeT8KQm4RD5owkZmBCdVoTrDOuWwWcCTmJZGI6cM49p+BCzBhGxuAfuBdwG+BsmHsTxAEQRCyhbwfBSGHiIEmTGTaMC+V2QnWzQb22/9uB1owoRyJ2JlkeUKUUmXAZcAtWuvbHMuXZLIfQRAEQRgl5P0oCDlEDDRhwqK1Diml3gY+opS6xRFjfzqwkOgL6Fngy8ABrXVLhofxY5KnnZQCbgaPOF6T4b4FQRAEIevI+1EQcosYaMJE53vA88CjSqm7MFWq/gdocrS5FbgaeF0pdStmRHAycAxwrtb6shT73wZ8QCn1LNAJNGitG5RSbwI3KaUaMSOV1wLzs6uaIAiCIAwbeT8KQo6QIiHChEZr/SLwSeBo4J/A14Gv4gjL0Fp3A2cBTwPfxCQ//wkThvHKEIe4ARM//wTwNhCeG+bjwDpMTP09mBdeshARQRAEQRhT5P0oCLlDaa2HbiUIgiAIgiAIgiCMOuJBEwRBEARBEARByBPEQBMEQRAEQRAEQcgTxEATBEEQBEEQBEHIE8RAEwRBEARBEARByBPEQBMEQRAEQRAEQcgTMpoHbcaMGXrhwoWjJIogCIIw3li3bl2b1nrmaO1fKXU9pvz3XGAr8FWt9esp2r8H+CVwPNAA/K/W+s4kbb8N/Bj4rdb6hqFkkXekIAiCkC6p3o8ZGWgLFy5k7dq12ZFKEARBGPcopfaP4r6vBm4DrgfesL+fUUodp7U+kKD9Isx8TX8CPgWcA9yhlGrVWj8S1/YMzLxMm9KVR96RgiAIQrqkej9KiKMgCIJQqNwI3KO1/r3WervW+stAI/DFJO2/ADRorb9st/89cC/wNWcjpVQ18ABwLdA5euILgiAIwmDEQBNyTiBk0dnvp7HbS5fHTyBk5VokQRDyHKVUCXAq8HzcqueBs5JsdmaC9s8By5RSxY5ldwMPa61fyYasgiAIwhBYIRjozrUUeUNGIY6CMBK6PQHe3NfO1oYedjT2sKOpl+aeAXzBwQZZidvF/KnlHDWrgsWzKzlhfhVnHjGD6vLiBHsWBGECMgNwA81xy5uBC5JsMwd4MUH7Int/jUqp64AjMSGQQ6KU+jwmFJJDDz00LcEFQSggQgFoq4FZx4FSuZZm/FK3Bnrq4bjLwS3miZwBYVSp2beftzdtZee+Wtpbm5iEFx8lTK+ayuUzZjL5iDkEpyxkUlkZpUVuBgIh+n1B+nxBDnR42Nncy0s7WghZGpeCUw6dynsWz+Syk+dx2PTJuVZPEIRxhFLqaExRkHO01oF0ttFa343xuLFs2TI9iuIJgpALGjdCZy2UVUP1glxLM37ps8fatERRgRhoQjbRGho30L3tJVp3vklF20YW6xYWh9c7nV9eoM7+uIph+hEwYzHMPxWOPgfmngRus4EvGGLzwd5JsRYAACAASURBVG5eq2nl1V1t3PpiDbe+WMO7j5rJp884jPceMwu3S0a1BGGC0QaEgNlxy2cDTUm2aUrSPmjv7/0YT9pWFR0pdwPvVkp9AZistfaNXHSh0Oj2BKgsK8Il75qJR8ifawkmCDK+5UQMNGHkdO6HdffgX/9XSjxNVAM91kz2lB9N/WGf4KhjllA1dTaUT4WyKgh4wddrPj0N0L4LWmugeQtsf9zss3gyHHoGHHsppcd+iGULZ7Bs4TRuvPBomroHeOjtAzy45gCfu28th8+YzNfffzQXnTAHJeEHgjAh0Fr7lVLrgOXAPxyrlgOPJN6K1cAVccuWA2u11gGl1KNAfBnGPwO7MJ61wuupddXBpOlQMinXkhQsXn+IFTUtHDZ9MicfMiXX4ghjTdijo6Rsw6gS8ZyJoQZioAnDRWvY/SJ6zd2w6wUsFK+FTuIV95XMWnopl599MmcPJwSxrxX2rzSf3S/Bk/8FT90EC8+BJVfBCR9mTvUkvnrBYr703iN5fmszt71UwxcfWM8ph07h2xcfy7sWTcu+voIg5CO/BO5XSq0BVmKqNM4D7gRQSt0HoLX+jN3+TuAGpdSvgLuAs4FrgI/b7bqALucBlFL9QIfWestoK5N1tIa6t6B4EhxzSa6lKVj8duGqTk/h2edCFhADbWzQOvZ7giMGmpA5e19Fv/R9VP1aOtVU7g9ezquTL+bSc9/Ft087hIrSEdxWFTPh+MvNR2vjVdv6KGz9Fzx+Azx3M5z8CVh2LcUzF/OBE+dy0QlzeGTdQX75Qg1X3bWaq5cdwncuPZbKMikoIgjjGa3135RS04HvYCaq3gJcorUOzy1zaFz7fUqpS4BbMaX4G4CvxM+BNm4IdyyD3tzKIQiFjBhoY4wYaCAGmpAJDRvQL3wXte9V2lwz+L/AdbxVdSHXX3Isf1s6n2J3lh9eSsGcJeZz/ndg/ypY+0d4+w/w1u9g8cXwnm/gnr+Uq047hA+eNI9fv7yLu17dw+u7Wvnfj5zEOUfNyK5MgiDkFVrrO4A7kqw7L8GyV4GlGex/0D4KhkjIkIR+C8KwsULmWwy0sUE8aIAYaEI6+HrhlR+j37qTbir5deDTvF79Qa675Dh+eMooGGaJUAoWnm0+fS2w9s/w5h3w+/fCURfCe75F+YJT+eZFx7D8uNl87R8b+dQf3+Lasxfx7UuOGRsZBUEQ8gkZ+ReEkeO156qX39EYIQYaiIEmDMWOpwk+eROuvkYeCL6Pe8o/w39cspT/t3Q+RbkyeipmwXnfhDO+CGvuhtW/gT+cb3LUlv8PSw+dx9NfOZefPrODP63cx9aGbu745FKmV5TmRl5BEIRcEB6JluJJgiAUCuJBA0CGA4TEDHTj+/vn4KGPs6fHzaes79P13p/y5Ncv5arTDsmdceakrAre/TX46mY49ybY9hjcfiq89nPKCHDLh47nl1edxDt1XXzoNyvZUi8z1AuCMIGQEMfsIv3GiY0YDmOEnGcQA01IgN73Ov23nY572yPcFvowfzn5fm77+n/w5fcdRXmJO9fiDaa0Et73XfjSW3DE+fDyD+Guc6F+PVcuXcDDXzgTS2s+cucqXt7RnGtpBUEQxgYJcRSEgqOuw4PXH8qtEH2t0L4nN8cWQxgQA01wEgrQ+di30fd+kOZ+zX9P+wUX33AbP7jyFGZWFkB44LRF8LEH4FOPgK8P/rgcVvyME+dW8PgN53DkrAquu28d/1x/MNeSCoIgjD4RAy1PPGiWFS24UIjkyWkUckXmhkPPQICdTb1ptw9ZmvUHOlm1py3jY2WVfa9Cwzu5OXZnbW6Om2eIgSYAoLvrab79Aqa+cweP8D7WXvQYP7rh31g8uzLXomXOkRfA9avg+CthxY/hTxcyM9jIg9edwbsWTuPGv2/kD6/vzbWUgiAIo0u+edC2PwbbHs21FMNHBvaFDFm5q40dTT0EQ9bQjQFte4+8gQIeyBgpbTW5liAvyJOntpBLure+QM9tZ1HRuZ27Znyb99z0AFeddQwuVwEPF5ZPhQ//Hj56D7TvhrveQ+XBV/nzv53GxSfM4YdPbefWF+QhIAhCAdJ9EDY/bCIFUpFvOWhWSMKXhMJlGPduyN5G5YsXWygYxECbyGjN/sd+RMU/rqI1NJkXzn6Qz3/pm8yqLMu1ZNnj+Cvg8yugegH85SOUrb6V33z8FD5y6gJue2kXv3yhJjJiJQiCUBB0HTDfA0MUPhppFceOfYUdkigIOUa6F8JwkTL7E5XAAPv+fC2LGp7i1aKzmfPZP3L5IXNzLdXoMO1w+Pfn4fGvwMs/wN24gf+9/C4U8OuXdgHwXxccJSNcgiAUGEP0/kbiQetrgfp14O2A+aemv92Bt4zhuPjCzI85xuxv72dDXRcfWDI3PyoTC3lO5tZWQdpnVnrhmMLoIgbaBCTY1UDT3R9mkWcbj1Rfw4Vf+DmV5SW5Fmt0KZkMH/4DzDsFnv8Orp4P8bOPPQREjbQbly/OpYSCIAhZJuxBG4bxEQqY76Avs+266zI/Vo6oaTYhov6QJQbaBGcgEKKsOPtVqsMROuZ76IGSvDDo/I7Qaa3zp8jQBEOeSBMM3/619Nx+LlP79/C3w3/CZV+5dfwbZ2GUgrNugKv/As1bcP1pOT87bzIfPXUBv35plxQOEQShwBii4yTxVQa/J+FiK5wflC85ekJOaOz28tzWJtr6MhyMGLc4nht6bL1pjd1eegYCY3rMfEUMtAmEf+M/UPdcjDcIr5z9F67+zPUTc9Tw2Evhs0+CrwfXn5bz09N9XLLEFA75+9rCGf0VBGGiM5QBlgUDrdCNvPY9sPNp8HQMWjXSFD1hfNDe5wegy+NP3XAEv4V0txzqEM09A3R7RtmAcQoxhjmoWmvqu7zUNKc/LcF4ZgL2zicmgdd/Tcm/PsfG0CLWXvgIl16Y//kBo8ohp8G/vwBl1bj/cgW/OqOfc4+awbce2cSzW5pyLZ0gCIKQDTzt5tuXqNMXDj9LvQsx4IR84c297ayoaRnlo+TGgxa0CnwwKMuIgTbe0Zrgs9+h+KX/5unQu6i79CEuO/vkXEuVH0w/Aq59FqoXUPLgVfz+rB5OOmQKX3nwHVbuzvEkkYIgCIVM3njewtbVYHnCIlp5I6uQC8IG+NC3wQjvk55GaNw4xBHy7F4cKwPNsgjYc8UVF/IUT1lEDLTxTCiA9egXKXrzdu4PXcDA5X/gyncdnmup8ovKOXDNUzD9SMoe/gT3n93OohmT+fx9a9lY15Vr6QRBECKE4kaYQ5am3xdMvkEuDY98Kc+fovcdPp1DBormWZ9ZyC5Zy0H09UaL68ShNbB/JbTtys6xRhPnDa+z9zsOhqJG2OBjWo6QYzHQQAy08UvQB3//DK6ND/LLwEcIXPhzrjz1sFxLlZ9MngHXPAFzllDx2L/x93MamVZRwjV/XsMuiYUWBCEPaO318eSmhphCBlsaunlxezNW0tCgEVgWI+0kZbFjlw7Jz0GYweuDdjlxmQtTgDR+LanuE8uCmudgzysjkyGLt2LPQIBu7wjz1bI40PLi9mae3tyYeOUYPy8KATHQxiMBLzz0Cdj5NP8duIbeM27k2nPFc5aS8qnw6UdhwWlUP/0F/nXWAYrcLj79xzXUdSSuACYIgjBWtPYaw6yjP1rIIFzcIG9yN5zzJ42hB21HUw9PbGoY5GE0ZKG0+UhOb9x5SCxjjtAadr0I3QdzLYmhtynzaR3yhbCB4evJrRxtu6HfpGi8sqOFFTuHka8WUyQkhYc+Q3zBFOGS2sq34M6cIwbaeMPfD3+9Gr37Jb4VuI6WYz7Ndz5wXK6lKgzKquBTj8DCc5nx4ld5/Kw9ePxBPvOnNbRL+V1BEEYZf9Aa0hPkNDdctpcrf3Ko0iwukIm8jZtg88MpmzR0eWO+Y4ikoMUe0+k1G7XT110PW/8Vkd8ftHhyUwM7m7IcmRH0mdymTCcYtoIw0AUH12ZXnuHg74faN6DhneRtmreaqpwjJBCyYkq5p+8sTnGjDHETjVluWeMG2LsiZZNub4CWnoEULRyyJgnZzDr5EhIdJhRIWPl1LBEDbTzh64MHPoqufZ2b9fVsn3s5v7r6FNyScJk+JZPhE3+HIy9g7qvf4Ikzd9LY7eXf7nmbvlS5HoIgCCPkmS2NvLUvcacgMmeXgrDV4bKf7cnzOobfKbQsTW1bX+pR70HHc7ZN1ZnNYJ9tNfY2yfdXXV4MQH0iA81h0oYsHTlXMV5HjTFysm2p9cd6L/z2sQ92Zjkqo3GjyW3qqc9su7B3xJX9CZozZqDbfKcyCFq2pzbg0uTNve28smOwZ2lklz+DjXM8oLJiZwur97YnbxDjQRsjAy3yTFCEiiaNzTFTUfcW7HkZQoP7fe19vjGZq00MtPFCYAAe+jj6wGp+Vn4jz7jP43efOpXykjx48BYaxWXwsQdg8cUctvq/eWzZFrY29PCF+9fhz6SzIgiCkCEtvalGtgEUgVCIgUAIt217ZOo4SYfWfh9t/X72tGTg7YkpLpAlAy2N/U0uLQKgtChFl0brmBwYZ6ihtgKw/QnjfUi06XC9H67imD9jjewsMtxKe2FjSOVBPyFSIWL0u6XOMGHI4HqkvKczMdCSX68R2W4JjInhkQMPmrbQWqOVi4yM3dEi7D1LEOL5xu62hAZ+thEDbTwQCsA/roF9r/G3ed/irs6l3Hr1ycybUp5ryQqXolK46j445lKOfueH/POkdbyxu42b/rExjWR0QRCE7NJjJ/srBev3d7GloTsS4hgY0kLL/JkVrmyX0ZbOjmdcJ3TNvg4OhPN5h2VQDC1JwvwuR+97IBBK2FYH7U5otnOxXEUxf4bfHQpFIGQlDskcS/LJgxYmhxX8RhaGOESIo3P1KJWu7/N6Wbu/g87+ISbcHophWIn9viDBZJ78tI5pF+xR7px7GIHobyKHxUvEQCt0rBD88/NQ8wzrTvgO39pzAje890jOO3pWriUrfIpK4KP3wPFXcNL2/+Nvx63iiY0NfP/JbVL1SxCEMaXVzoNVgN82yFz2GzyTKo4NXV4au4c2DMKdg2JP85A5YImPF3vsxm5v1DuYZQ9aeFXqYilxUxQ4c9DSPHTGHfg4A21rg11AQsH6/Z28XduRepqE0SZkd+TzwYMWPrdBnyl0NhZH1FGDOQs7y0rbkRiJ3X1mAKTTO9J7Kk1PuIMXtzezak+KsMmhsEJosD1o2cXjD/LYhvpYz+mel01+aDLCv4kxnKg7HjHQChmt4cn/gq3/pO3M/8cnN57AmYdP56sXLM61ZOMHdzFc+QdYchWn7/0N9x7+MvesquWOFSNPVBYEYZwR8GR19LfLM3gkPNEcQZkc8e3aDtYkyXOLPVB458MM3cpWOFh0oyFbNCcsfJC48x0KOYuE6JRtVV8TRYH0Qz2f2tRoCoEUlcQsD0+R0OMNRDqLOa3AWfuG+S7Jg5yf8DXwtMOOp3Jy/OKOXUMUq0h/ACD1sRJ0+i0rC8+OsBdqZAbn1vpuapoyr0bZ6XhevbKjhf3t/Snbx0wB4PSgZZlwBdwYeTwdqa912FDMYfESMdAKmdd+DuvvJXT2jfxbzdmUF7u57WMnS1GQbOMugivuhJM/yXsa/sDd85/l58/t4KE1B3ItmSBMeJRS1yul9imlBpRS65RS5w7R/j12uwGl1F6l1Bfi1n9JKbVJKdVjf1YrpT6QljBBX/qVv4J+U+Lcl7jj39jt5dWaVg60xxaUSPR0T9qvG0GHT9kdlMxCHOOqOAaThFoNdKW5O00oHL6ZhgcN4LEN9fiCjk5VkomqrWQetG2PmaIbDorqVjG7+bW0ZAYzv9qOpp7oMYtKB7UJFwzJh3QbispyLQG5OBHOW2KSp46y9q3QuiN5o3R3NnTjwYtqnoV9r43MYE8iwzObG5MXEkrAwc5+eiKe3eHJ0zMQYENd8t95U/cAK3a2OKYx0vZ/edJ/dcUZaN4uaN42tiKM6dGE7LHxIXjlR3Dix7hNf4zN9d38+IolzKrKhwftOMTlhg/9BpZ+lgvb7+O3Mx/j//1rE89tbcq1ZIIwYVFKXQ3cBvwYOAVYBTyjlDo0SftFwNN2u1OAnwC3K6U+7Gh2EPgmsBRYBrwMPKqUOjFNodITvrfBGCot2xOu7hswHaRe39BJ+mmHRfl6md34Cq7Q4GlDLEuzoa4Lj98cN2LXpLdnu7HDMNq7ArY/nrjd/lVphbG9XdvJO5FOXvqSeP1GjmDIihpCcdvHBGM6O7ahgKmImALL0qzb30lvhpXcqsqLBy0bs/LrTvy2J6G0MiJFzslh2oBS4ApXK0w171dKGUfgQbMs433vbx1h8Qk7ZDMub8ofsjLMS0uiS2sNdNVlJFFtW3/Cwkd99nMt4kULnxPlQuX6fuxtilZeCp/L3S9Cy7YxvU/FQCtE9r4Kj90AC89l49If8NsVe7jylPlcvGRuriUb37hccOmv4LTP8YHev/OrKf/gyw+u561U5WoFQRhNbgTu0Vr/Xmu9XWv9ZaAR+GKS9l8AGrTWX7bb/x64F/hauIHW+jGt9TNa691a6xqt9c1AL3BmWhKlnUMRa8jF57WqkI8ZratRwdjOTSL7b6g+Q32nx8zl2LaLopCHcm+jY+V62Pww7f1+9rf3s+GAMYjc3mHMAeQZ+lkYKdQR8ELLjpTCp5MrB0Ao9hyFo0he3tHCyj22HoPmQYv+e09LX8rdx1+bXl+Qg50e1u7vHGK72I64M6wykRxjQn877HwGOvY5k+vygNEVorHbO+g6Ov9S2jKnI/73myUPWsoiIQkGTIaDch4kzjPvDQwzVM+5z6ZNpvz8kJtEt9l4sIvVCXLTwqHakabaQqNHJcQxJfFe/sCACf0NTzgeH+IoBpqQlJYd8LdPw/Qj8V55H//18DZmV5Zyy2XH51qyiYHLBZf8H5z+RT7kfZT/Lb+f6+5bw/bGzOO1BUEYPkqpEuBU4Pm4Vc8DZyXZ7MwE7Z8DlimlBrk3lFJupdTHgAqM1y0NwTJ8rdov/IOdscZIcfd+Sn0dlHbF5rtmVtDA7PtAp4c3drclbtKx1+zX6THracDdvhOAcMRVyNKxOSOJcJT5DlkWdR0egsFQTPXELQ3dxlhs2gzNW6ArzVDxZB2j7noq9z5LiS/aCQy3jO2UxnfOo3+39Q2YeS7T9H66Av0U+7vxDdHp3dsWa/glmlB8TLp7PQ3QWsO+tn4ampvNMk979Og5LIQQYRQ7vgc7PazZ18G+tticqGiRECep7gHTvq7DM6hUf6IrmbSYWPzy4FBTawyxv0QyBGL3majC6c6m3kH7bOjyjvhapLN5JMU1cg+GvX9B4+Hvy14Z+5TPzF3Pxf4dX7Vx0G9j5PdpXYcnrXnUioZsIeQPng548GozT9cn/87PVjSyt62fv37udKrKBodOCKOEUnDRT8BdzOWrfo12BfjsH908cv05HDItD5KtBWFiMANwA81xy5uBC5JsMwd4MUH7Int/jQBKqSXAaqAM6AOu0Fpvzo7YsfQMBHhtU0OCDlTYuPKyfVODY2n2Ovn+oIXbsnC7XLE1QZzhh3bH6Z0DndR3ebn4hLmUJJ1vzGn0+GnuHaC3qYfdLT1M9kRL2Pf7Q0wPVxBMEFK2r62fTQfj81eSaOkxhmdpoAd/6XSnyDbpGF06o9Fq965nmdXSQ/2C1KmJvd5AzDB4Ig1GVBE4FBhUKRLMhN1zqsqi+ej7V9HvC7KpaDKT+nuYVxU+eOLwz+ESDFlYmhT3hwPLiub5ZFGGRAwEjJ4ef2znO/EvLp7BS9cfMJ7Ty06e72g2uF3MJO/x+ZlO0pzIcGj7LMZNN+T+djT1MKnEHdNv8QZCcSGGmV+XdLaI96BtrOvE1eGlOBgCt8uEflcMvxq5P2jR2O3lsOmTUzcMxnkv40/yKAxeJLx/EiAetEIhFDRznfU0wNUPsLargntX1/KZMw/jrCNn5Fq6iYdSsPz7cO7XuMJ6gZuDv+Wzf1iVpIqYIAgFxk7gZOB04HfAvUqpExI1VEp9Xim1Vim1trcng0md7Q5KfZc38fxdDpzrYxLvI4PPyUfqk63zBy2e2dLItkYjc9iMsbQGpSLbhbfusCsQppTVcawi2zjw+ANUd29nStdWZ8OUvc3aBNXfOvt91KeYN8w9lPfLcbx1+zvo9kRHsJUe7Phs6/Px2IZ6uj2BwR35NPus8acq0Xb9vsReuOaeAVbtaUt8/ayQmfpg22NQt2aQ3GtrO9jWEBvVsT2+Kp92XIPIPAV+GBh+NMiL21t4ZktjyjZ7W/vYvnUDbP1nwoGAsUBZQSq7ayLha0qZEEcjR4qQtgxz0JyeY62Te3PHwoOZqPorMKh4iLnfMrsWNc2O556nA7Y9NijPdSDO2xz1oBlaejz4gqGsldnf3tjDhrquhPlvPQOBaPGhIRn7axVGDLRC4fmbYd+rcOmvGJizlG88sol51eV886Jjci3ZxEUpOP87cN63uYwV3Nj/Sz519xsJHwiCIGSdNiAEzI5bPhtIVr2nKUn7oL0/ALTWfjsHbZ3W+tvABuC/Eu1Qa3231nqZ1npZZVUlmXZuRuJBiaRvpLKZ7G9XyEdTa2tk+Uo75DFc8bB47wt2HgiQME3fdEzC4WKpjwYu20ALBIIJi5JkMgGs1pqVu1tZW5v4uBrT4XvXomnxYkQ7fI6O1cFOL9tiwtLDG0Q7seFJpDsSTHWQ7HQHQhZb6rsdDQeHR8WP6L9TF5vH5vEH8QVDvF1Th6dxZ6Sqny8Yit4rIYdM3bFFG8Id4ZhKlkmJC3Hc+wrsio8ATk5P7Xp0c9TwTueYm+u76dlvV8n0pc79yxZKgbKi56y6ewdVvbvQ3fXRRtoypyNVWXUrCLUrcQcTlI9P8CP0x3jQ4rxpXQeMkR300d7vZXdLX8yzINFvOqMnRZrPlfhBBCvePktjPzuaHAZa8xZ00E+JP9YDnqygWlTn8ICQO+bvkRIuthTGsjSv7Ghhb1vqKQCiAmbXIMvkeS8GWiGw/n54604443o45ZPc9tIu9rb285MrlzC5VKJUc4pScN634H3f41K1km/1/oRr7n49Mt+NIAijg9baD6wDlsetWk7yfLHVSdqv1VqnSgpwAYNrpY+IdD0+ydulcmY1dnvZ2dwbmcR6dtOrHDy4P7I+PgfC5e+jxN9pOhCOUeywGOEl2xp7aOz2mpytQTJbhCyLQMiK5Fv5Q0k6vOGOcIIOS7zGsb68ZOhIrokzDDRioKWqzhc/ibVlRfKV3EpFVhf5usDbGTMx+Bu72iKGye6WPg7U11Pkt42/BIVJ3Eol9WYAvLCtmee3NjOjbQ1TurZiebvRWvPsliY27Gs0Hq7+JPmERKPlXEmn23H4LuI6x5HCEml0IrfUd1OzZS1Nu9YP2XaQBOFOr+WcB2sEHXJvJxveeoU9rQ6DL+gzhVAAt6eNeQ0v4O4zRkJxwFwfHZmnTkWHJFLlHHk6oLeRaR0bSYdYOyfOE9e+2/zb18c7te10ef0xIZGWFaK1tRUGuiMXNeFvLuaAwwhHTHCPjqiKYtBn7NwEobdOnPmYT2xsiN4TymV+Hynu8XQoKzaGnj/OQxiwz2XaE8TH3w8OuQfnIabg4Fpo3xPzzN7bmnqAQnr3+c7BdfDUjXD4e2H5D9hS383dr+3lo6cu4N2LZ+ZaOiHMuTdCWRXnP/U1Jvd8j+t+/13++PnzmTa5ZOhtBUEYLr8E7ldKrQFWYqo0zgPuBFBK3Qegtf6M3f5O4Aal1K+Au4CzgWuAj4d3qJT6KfAUUAdUAp8AzgPSmwstzU5Sc+8AbQ3d6KqKtNonPlbyQ67Z18Gk/n4W2Q4bV5z96VJq0FxgxYE+s0vlGmQPqYifypAw1FFrtjX24guGWDDV5LWEQknyuzKsXKeSnNYOT4CW3gHUtGiNj8313UydVGJvZ2+YyjOibZPO3kFj9wDYeVpuh/DTm94AV3WMAdje52V/Y5CisgoCIYtZLWby5/oFHxgc4mgfwq0UwRT3iaV1pOy72v0C1pwTQFcR2vYU9E+LbRxn7IWvabKQz9h5ppLcQFYQ3Eny2ps2w9RF7GntYz7RKQ0yQdneWII+uj0BApZFRoka3fVQVg2l9m9n90sEWzvYWryQI2bay+rWQF8zTJ6B22sKyBQNxHpgW7oHWF9bz9FzKo2BoBhsyDvPTb8pXOGy/Gb5tsdgzokwbdGgczgQCCX3oKGjfyuFto0Gf9ACu8swpWsr++sPMPOwaTD9CGpLFrPRkZdZ29aPBhbNmBy73zB9zZT4XPhLp4LWlLRsgsoTHFMrGBIP8iTPQQuELHr7/TF9m1gjz35SDOF5cj57Yp5DzhBHvwdKJhEIWTy9uZF3LZrG3OrylPsNEx6f6Ojz0+OOXtOAXUnVFf/72POyMcDLpsQuH/Q7jf4dc32HorMWOmsJVS+KLEoVsg3iQctvPB3wj89CxRz4yJ8I4OLrD29i+uQSvvOB43ItnRDPaZ9DXXEXp7t28L2um/nC3S/SlSA8RhCE7KC1/hvwVeA7mDDEc4BLtNZhV9Gh9ifcfh9wCfBuu/3NwFe01o84djsH+AsmD+0l4DTgYq31M2lKlXKtZWm2NfSwoa4bbyBEMEHpdbMbK/Y7AX0+83wpbt8JPUlyfzS4EniPpkwa3AF3h7y2FeGK9UJpTTA+ZyNJxy7sTTrYaSagtRIYRibNJc57k4JE1Q/DbHTk5IW7XB39/og3papnp+lAJpk24Og5lVGPgT0/WJMjl9g9xLQG0zo2oHc8zeaDHexrjc9BjJU7Yjxl0POyLA3NWyjxJwkrVbGFNkI6SQc0Hq3Z1dxrQjLj77HmrYm3GeiB1p1wYHXsSRhi3rjY41rRebqsICtqWuxwW7M/TyBIR7+fjXVdMZ7KGA6sThiKqbQ2hnjLdvD3RY9nDwZYkXNl9rvPrrJpwuDCXr0UBmc4Udqn/gAAIABJREFUZ05ro0MoAPXr7IqDsbI+t7UpUgwivE3seXCuMscMOdqU+BzXu7+dzri+xMaDXakL6bTVMLPVBBKU+Lso6txjZI3DCuci+j32HuJjHGOpae7l9ZoU87/a9138XGyDjxtuHm5vzn9MmX37fIe9XTXN5nrtau4dcnqj8H5b+3wx03UEbY+a2+lh1tr0t8HMTelk0HVzXKN0iuFATEVN57NsKA+cGGj5imXBP68zI0BX3QuTpnHnij1sb+zhh5efQHWCl6uQB5x0Nerq+znRvZ8fdH2Dr/z+2QwniBQEIRO01ndorRdqrUu11qdqrV9zrDtPa31eXPtXtdZL7faLtNZ3xq2/Rmt9mL1+ltb6Aq11XC3m4dPUM8CulmhHvncgyfPB7uBEvA0pKGrfCvtXGq9BwwbnTghaVsIcsHAIULijom2vTSJjqK7Tgz8uyT/hBMsJtnUpKB+IL7SZHpHS+TryvyGwmNa+ntKB1pilGkyoWAJMWKQdRKn1oEJP2p6fKXZZ9N/l3kZClt1hj2un4v6ltTGcqnt2UdW9cwhdouGaGtAqScBTXFGFsFHjSta7U9BjT5fQ5RlgIDhY7vipD7TWPLahnh0tdt7OQHekA25pWPnORpo2PE+ZN3HHvbXXF/G4uu056zo9/sF5WcC2hh72tvVR297PbmcIWBrV9ZS2jAHZvDU6GbdyUdK91/53eC4JbbePBs8qrWnuHWBwbmT8tU9wH+57zUw0HcbbSelAK8X+Lip7dtl7iQtxJGKhRL28ziYxIYI6YnAX+7sG6R6yjLGtreh+wnJOa19nBl4A3IMjeiytzQTMO58Gf78JcbS3PdDRP+i8ewMhSvzdZsqnRNje96EMtPD9EP6OGmgKXzBkwjltL3L8Kd/W2BMziAIYY66/zeT1DXTHOJZLfJ2RZ0nYgxYTZuxLURgnRchrZA+hALTtTr4PxzQKmUShioGWr7z2czNz+UU/hflLqWnu5dcv7+LSE+dy4fFzci2dkIpjPoDrUw9zRHE7P+j4Gl+581Gp7igIEwWtYf9q2PtqwtURA2hID4fp4FT01SZvEu4ihF/6XQeiuS02te2ehDklDXHhNaaTGrL7jlbM8vY+PxW9sfOxJe5oJDDQsFJ7cxLloNntZ7a+6djr0D0bl6+Xcm8jM9rejlme1BNDuIKfBm06n3W2529Sfx1ojZWg2psV32nHdDDjw7pcidopqOrdRWVvig6dgx5vMLXqygXd9hQGnfsj1encSXPQoKal10gTcWLa/yixw+WmHR7Tvtc7gLKC7HFU6wvrGrQslNa0NB5gevs6lBWE9ui94vWHWLWnjXcOdEJ/G257sGBPa1/stU9gcMXML5oghHDd/th8QKWtBKGz0fOgccfkHjnttUnhaSBSedCwr2EiL5Nz3rHdL9k5hNuo6qmJ5iQ69xJTJdWy/58k1E8bA63I38OslpWDjPttDT1sa+yhxdHPCHvjyr1NlIUHLBJMAq01xhEAEPDazyezbUuv41w6csJmtq5GN20eXKIeIt73oUIci9u3M//gU44wwfD5MHrvaOoxhk8KItsO9MCOp+jZ9gL1XR7obY7cLkWBfma2roo8S8LP35ifh7NYTDzagt7EA0yRq9W0CRo3mCrribDPk+UqjvGSDoUYaPnInpdhxU/gxKth2bUEQxZff3gTFaVF3PIhmZC6IDj8PIo++zjzS738vOeb3HTH39ifoHS0IAjji/V1XezfVwP9raaj2tcKoSC9A4FBJa0heQkQ5egoukKJB3jUkKaLxuMPDmoxpWtr1NvhiDRUOkSJpwnq3opp73YpKvv2Rv4u9ndRvP2f0LjJrkRnewGTeNBSRHeZzs0QaMe+BxlbEeNPo+ywNiuuI7q1MfkIebij5g9aMZUdp3ZuoqqnJqGBlqiPlciDFn9xtdYoFT+BdmLCe6rr9MRc5aBlxXk5HQfpa6a411R1LGvbaq7NnlfiJXX8y3HxIdqBdznOXygAWx9lXsNzgJl8vLHbi9LG0LFsg94Y1Yrq7h3Q8A70Ntl7Nvtu7fXB3hWRsLtYLdMgrsN/oL2f+vYu2vqdRoLFzvjpBIheL61cvLitiZJA2Jtqn1nHb82KL2ozqIhG2ICJkz3BfRz2IrktX8x+DnZ4eHNvG3vb+rC0cpT4dxwH5z2sKe07wOyW1wEoDsYWl+j3m2sRDMuuYnPLJnkOJn1SmHspaqkOvrftBY0bBy31+gJ0dLTjDjoGe5TL9sKlNtBK2o2R6Q9X/owMXDnMErtaaVik+GdlJOza/t3XNPea/FEr+swrG4id8PqdA7FVU82OUg2ga6h93fFngns2ZBv9tkH5xMYG1h/oZG9rnxkQCPno8vhZU9eXUUSVGGj5RvdBeORzMPMYuPRWUIo/vrGPjXVd3PKh45lRkeVCYsLocchpFF37DNMnufn1wM3c/LsH2NmUwTxJgiAUHE3dXlrDVVybNpvpUerX8fKOFt7Y3ZZ+iEsG5Z1T7bMiSaXf6e0mHyXaRTej3lNa3x60z3hvTEVfremottWYBZHwruhGliuDAklpnJSwMZF0BFoTMRqiHV7TNmIYJ/XWadr6YjtO1eXFlHsaEm6TsPKd1oMKmagE2xT3xYYBVpU50hVatjOn8WXm1T+D21EWPhyCB2YevH3OEuF25zIYsvD4ghFjuaTT9tB5HLk6WlMUNNdqY10nkesVn+8Y1s/bSf2qByOFQJS2aO4doL7LGw1h0xrLVYI/aKGVMgU0INJZDe8qvppezMqIlikIxV4fDcxreCHGO6u0RXNX9NyELAtfMBjZs4VDPhz3lMMI1ymrfYajE8122xp7BuWGxbS1DV7jmTbHCIQstjR0AZqOfr8x2mO8aeFtYz1o5V27E68jOiF2h8NYHew1Tnx+LY3DKBpsoEXu9TjPotaat/a1sXfVI8xpejm6whXWOfnzayAQnTLCF7B/s1iAQju97VYwpiKsUrHFiSwNq3a3RaYMichmBSJ6BN1lMet8iQp7hFIYTclCHHUIV+t2Y5yFBzQiYb+aug4Pm+u7Wb2nHUIB+nxBLFU0KHIhFWKg5RNBv5mMOuiHq++Hksnsae3jFy/UsPy42XzopHm5llDIlDknUPy556isqOLO4Pf4yZ1/SjyCIwhCweMPWdF8EohWhLMTz3u8gWjhgBRFMrbUd8fkcAw1Gj0SnOKGQxxrmntj8n/iDTR3yGvnLhna+/2m42R31ltmnUPnlBMisjvzb4JFCapWxvUKB3kVnac0iYGm0ZEOdzhvb3AeTHTbyX37mX/waft66UERp+GOv+UM9wz3VRN4BBN50Ipi+9gAuP1dlNv5fzNaV8dOldO8FXfIa1/v5B3sGKOgegEAO5t72dbUE/EottrzcfZ4A472mqoe23PR5QjrGuiBrf+KFtaw8exfR2P3QCTs03kfhs+tBix3iZ0r50YrF91ef8Qzksrs0p37mFv/vDk5QxnpO5+OyuUP0muHKsYbaM5rvqOpl82v/D1iDDR0+2IMgMjk7DGd/tSGTfgMKG3k2JdiPq2wIaWsUES/gUAIpXUkF88bCEbPpeM8xBTL8PfhdRgWOs5DHDYwnaHMg8JwHYalK+Rn/sGnmNy3H5enNWqg+HqprH0mYsQDhPxe44mNy9PSGvp90RDEMk+jPVLhRqNxWT4qevcy/+BTlA7EGlDvHOiKXJPwNBxKW7HGGWAF/Ty9uZF1+6N9pic3mTDCyp5dqF0v0NrnGzT9QMhhlCcK6zTnykGSydmDlhX5HcUoDkzyNOJu3QYtW2NjZUOBmDn3/CELtEVpkQuUC08GVU/FQMsnXvhvOPg2XHY7zDiKkKX55sObKC9286PLT0g5d4qQx0w/guLrnqd06lzu5If87g938cqOlqG3EwShsMggYivVXEMmP8dpoGWwY+cxtM6oFLTSISyXe/AcaQpiQuO0Zn+76cT5giHe3NvOhjrjFQBFoKQat9t0jHSccektn02opCr2wGFPXBKceTFaw9u1HazaEzdqrgcbdoMN2+h5NHk8GpflN96v+G0VFIU8kRLoAAPBEP6Qo+sb7kxrndiocly3SJiWcjN/iikVXupLNuF3IrGj+4qU0C8qA5fxwEXDJu0Jwm2jo6alN1LRMqnRbwXjPCRm28374nNqEhhomsiUAMYTo9jV0sdrNS32+uT3rvZ7cOmA7fmMbTe3PnldHmcoqnPsYGbrKooCvRFvXficOEWY0rUtqkPEgxbVPUbe9j2w46nIn/6g6bCHy7eAuTf3tsUatuGc83A+1bTODZH9ag3FgegAzNv72iP7ivGjOfp7Hf1+erqintB4A62k96BtFDgMtLhbPxjSkd+iOxTNs6xoWBktoNO+B4I+Jnmi192y55Jz6hWW0uW4h6Z3rGdy/34zbQBQHOiluns7ABW90fBo4P+z995xdl3lvfd37X36nDO9z2ikUe+WbLn3BrYFNmBTA4SEEFrgXkIab8IFEl7uzSUFYpOASV5MC2AIBNNDxxjH2MYVd1uS1TUjTZ8zp+31/rF2WbucKbLKyN6/z2ekU/Zee621y3l+63me34NVHHOvJEvzrAYLcjy5XxEzp/i6rnrYOP6ET/hHJ9a1WhUpIVGZpO2wPx/V3UZ/BtURCdk5PM3De0YoVjwCOGmTUsOqqNkuT3m5eNKCx75D774femOSgFVDCIEUhs8D2Dj6aORxHcQEbbHg4f9QxajPfjtseDkAn/3VTu7ZNcIHXrqezsbMHA3EWNRo6if55h9gdqzmE8ZH+drnb+Tzd+482b2KESPGMYfmLapZ7Do8xVO7PQn8ZHmUvj3fdYvl1vMc+AzoORTRnBbKNStkEEfWK7Ohr2xXbSVCf+6LgiEEYQpj72erok3MVFQOi/255ZixUTlcwQ8OPly3jwAP71OGmFErUZs6wr7Rospp8rUpQ6RXJySW9AsXWLainWGVVI8Cw3NIUHA+dx2e0j6z3PEIWYsg0hGeGTPh80i2PvNN2HE7s0GFn0acR+EpUHrb1l/IXSjRDxJcvwfNG7tD0KTwQtSkDHjQIo7tKfiFPWiGnF8h4eDCdbI6ydRMwKOiCWbkpnVBCJtk6deo3o999/nacXOcAjloQbl0x+PoD1N05kN69z6OR83SDq3adZUXwUcQVLvePSpnxigM3xcqnh30BB6cmHHz4J3rQMian8hJy/Zmeh/q4Z/OuJxeGgGF2WxxvyI7lv/e8ylSSkl65480r6XTFxXi6OvzaHRKSKIyoe3pNOsVqrcs5c8tTDxNV8GznX1zIgzId1GxpAoNBp48NMHhSe+5UqrWEEh+u2/cJYkP2aUNDKukOjC+zxMHsWqhOnoSqZ17g6ouajOHQm9M0BYDhp6A294N/WfBlX8NqB+B//uDx7hsbScv39p3kjsY45gg30Hy97+D0X8GNyZv4sFvf4IPf/uRWQ2oGDFinDrwrYADz45MMzRZYrRYJlNUHoXOQ3eAbTzMCm1VP/hD3t+SdY0R58iWlDy4Z5R7nx3RxEhknUK0Cu3Dd7nhhzuGp0LhiKAMtNGi36OmhyIpn5ktAy6lu/LvHHe6HDS0BbohVqlZPLR3LOS1C0JISdfBXzD20Pcjvw950KRFy4gn3FCzJL37fugq4Dk5ckY1Ov/EMfyNiX0+m32sWHHJoSeP7pA/v6Gv7+e+NhKYpn/+mDzIEwcnQqFabt+lnxD4EDDE9fM9FWivnvR5yMuljcu/v/feIWWWlAiHoKE8aGpbK9BEuP/Odz37fxj5fcdR5twHSww4OXTJir/UwqR9zUlt0qSWWzddrjJVqroLH27+kqxDmAPQy0v45j403zrRt0jPDM3qXdXzO//7qSEqNcurYegeIty/scMHfGIfyeqkL4SX8qS25GAfqx6HkGHCny4dgeIou45M+9rQFw2cczBT8as3qgaNwDUWfT90HVSVVDzCpZ5azrrH3TuPuPn+2ZRHZn35ZwIQgkcOTPHIgXEqNYuxYoUdmpibJb3r2AlNdO01+9jFSpWdw5NqviMWmozaDBx+ygun1cY31zUUE7STjdIk3PoGSKThlbdAIoVlSf7saw+SNA0+8vJNcWjj8wnZZsw3fgOx/BI+mryZ0p2f4h1fvNf9AYkRI8bzA2PFsm9lPVUeoW/Pd2bZAxLlcbdArZA1TWQg4CWR0JRVq9LCUuE8eh6NqjFVo2HKX8+qHhxjTshaaMHIXfH1/Qx5b4q2SqRhe3OcMCUZKArsg+ZZeHDPGKVqjSN3fhEsi2K5FkHqoGXkAQyr7K5kB/vSOPYEiUOegZQt7idd8jyEalySwsRTtA3fjWXXFTOskpKGD8Ax9lJDD4W+K9f8xmXVgnRpiO4DP/N6pQlDqC3tORaChMYgnFP76P5xJS0egZmyFTbmll9qjz3oQfPwaKC9ermMEdQJq1bDkAHSrJGMRGXS7r90VQWlYeKcj2xxv6pNNQtBq0XUQdMxNFnim/fPIoEO4YRAwqTCIf9mSA3VJpcVzyh371mrxiP7x3n0wDgP7hnlwPhMYPGinkczGgdHizx2YJypUs3n6VXhtU74o7pGUyV/nnqIz2keNCe/0KyV1JzPhmoZhp/0KWlGOX31BaGR6XKk+qzuGdJRqVlMlasIKanY+abVZMH93iFdNfeZg/1/OAdNF3SJgvPcajt8L0gvH1EKQW5qNw3Te32PrWK5Rtvw3TSPPGQfV1CqqjYesD1jpr74JCW+/ECAaom+Pd8lO3MIiWTH0BTDU2V/SQINrUP3uII5AunzoBF70BYxpIRvv0cVVrz+36BJecq+eNcu7tpxhPdvX093Uxza+LxDqgHxui/Dmmv4m+QttD3277zm5jt9NUxixIhxasIxpJ885M9LSZcOR23uGme5qd10HbqdjqE71RfSckmE80O+tE3VqUolTIQQpMojtvy5/6e+WpM0jT1OsjIR8ojN2fe6q7rRxueuI9MIaWEIGJkqaUaq35OSS6mxSAQj01VbYly6/TMMAZVpfvr4oUiltUR1Sm8W8JNSifTnUQWGoa9cZ2YOuWFX6QP30HbkNyFjSLcVo2ZEICjYuTUSGVGvTs9J87xpAklilhplUdh1eIpMsNh3tiWSENSk+qyUblfvzWygT9GYqdRUmKqN6r4HQtvohnvjhCrAXJFeHywj6RLzdOkIPPYdZLm+crE/P/LoIkmkrEG64PtsfKYSygvT4XjmhJR0DP03bQd+aX8j2Ds0wr07hilV/eR0dNp7b8hKtAdc1Depjzz6MyZLVfaNFd17zFnU0PP5hJxPeKckVTriyzszrLLPYxflObeQITXNCH7m+/DA+AxPHpzg0ESwgLvmbdSwV1MptEzHA6oTUqc8Q9SR/dezmGeYq7O3Hjrs1rXTmpypWGRmDrkLV2PFSuicWVJ5xe7ZdcQWffL3t/HQ3YAkUZ1k5/A00/aC0e6RaSZL1ZDX2vDV5ZNIq0ai4g81rYeYoJ1M3P2v8NCtcOlfwopLAXhmaJKPfPcxLlrdwSu39Z/kDsY4bnA8pqtexEeS/8amQ7fx0pt+yQO7R092z2LEiHFCIclO7/OF46mPa1i2AIRDcnqaMpyzvI2+5gwCj/QFPWh7Rop1vSXRPXBeRKkHKszYBr9C0JCyyKZMuy6RiNwm54QaCUHZsjgyVaakKUGOTlcYO7QbMR1NZKPwrQcDIhZCfxkM1QyEAtoETdQhnoYQCERd1UjTYNZi001jj3n14fQuymDhbhl5DL1fNSnD3lC77lhQBrzmNhWQzic6xLGY6QJUnt/jTiHqWgVr6MnIvgdhGWntdSokAZ94RkmwJyphtUN9EaNWmuLAeLQE+WxCI8ahh0PS+EOTpVBemI58xln4UPlg/rLskqkdv+a/H/XmezrbGxLbifROz0LQdNLlEN2kaaAImhNYqI7viq6giMGBwOKtkDU6hu6kffieyGMdcVRVA7AseHCP38aYLFV54uC4JmIiQyHV05Uazx6Z9n0mkWREmECVXQ+3F5bry120AqGCzn0qZeja0efBge5d1Ic4Xa5qBE0oz6Tw30fVmnYOhOTBvWOhY6q2tBqUllbvD5CaJH8l4Ko9MlUKea3dnEz7feuR++g6+DPb+xgTtMWJ3b+G778PVr0YLnwvoFzD//Mr95NOGnz0hs1xaOPzHYk0vOrzsOJy/sa4mZfKn/HKT93JN+7bc7J7FiNGjKNG9I+uiDA2QJGs1iP3hT4XVg0ZIGgC6CqkERMHQPhXYB1PlMRg/1jRJSCzoWrmANzwHEEtRGwALJGglshhVos0jj3mG6Oww+ws2/vmml3C70GLKq6s2zflmkVp972BQsZ1UI986gQtQEbCJMiWQHcUsoNNCYEh6ufg1CN2DhqmdpOZ2Gk3rnvQAg3K2QlInYM7nQzNhRuR6nhpNGKQmRkKNSWNRPj4R54JhGKp8QbntJLIu4sIoK69VNkjAFJKpJEgO73XLbJcD/sPHmLPSDRBG54s89t9Y5FE1jjyNLI8HbFXfRgB2yp4jnPTe2jY83P3fS2RDRnj0ZivzabG4REKhxzZXiPtnEalPzjExRHLiIKjsuo/avR1Nj5TdVU/53slSglWKUy6xx0Pkpanp183obBZ+4gd+SRBgZtQ6LGskdCKdOuhl08emvSR0lR5RBE0rcmokMkgQZMhD7f/+TXbvVqphb+TUoWJOuQ7Wzxg96U65yJaTNBOBiYPwa1vVCGNr/iUm9H6sR89wYN7xvg/r9hEV6za+MJAMgOv+SJi+cX8ZeUm3t1+L+/5ygN85LuPxuIhMWI8j2DUEWjwFSrWUK5U3RDHRHWS9MyQsv+GHiNYWFgivY9sg1mKuQlaOd0KwKidx+LUBAtDkbCWkfspTDxN0lFRs0MUhbRI7/oF5uT+UIijt0LuteXkqQWfcbqBblaL9jj8qpKWJesaNrpZFVx9D6fRSHefsab1YYKGMuRL1ZpPXtz9fh62eM3C9hJ6BDYzFBYSqCvQOBscD5pV8wmsuDaiQ+q1665xPFzOQArDN3ZHMbAamDDTgObR3/r3NfzXrkDShifEIQFqVTKBOliRqEXn8AA8sHuUYqXm1t6rJAta+O/C0KOljXgFomf/rQ1eg1GwpARhzItsO8dNGLanxz5XB8ZnQsIYUeG+nmpm/X4tJLQZYLpU5aG9Y1Tc481+AVZrkoItuBMFoXnQ0qXDtIw/BviFP5KGwLA9UgYydNELaSGsMt37f0KyPEbb8L2+SIP9o0VfXm/UXOktJjVCK21BoyjVU/055JwbhwwGFy50mHWm7OmhSao1v7CMmofYg7a4UKvC134fiiPKe5JtAeDXO47wzz97mldt6+eqjT0nuZMxTiiSWXjNlxDLLuCdY3/P/13zJDf/4hl+/5a7VYx0jBgxThGoH9xqoiHiq2hSsaw9vG16ZojhiWnXO9E09hjtw79WXptxJZpg4Bnfo9OVUHbRfIzKSrKR8cIqX7hRPTl3IaVrTDlGjZPon5veS2ViyDbKnER920MV8KBJYbqGWNAroUK+AGnRNPaI71gOagGCpn+ve7WC+SvVkAdEOkOjmshGkiTDEIwWK5HqikEvTBSmysroHZ4sUb7/VjoP/TIUGSOx1+hDaoz1jbeaJV2DsWbVeOKgZ3h6mi7zDXH1m4E7hpRXJGiI1huvzztiVUhp1bktSyKtipcPNAsSsk5IopRUbGK2b6TIwfEZkpUJZrLd9tfzJyKrOwv0NmX1mN557TefxQ7LNfhVSORsELKmrlUpaRx7LLIAuIP9Yx5ZcBY25kPQ5kLKNNyC6aDIYalac3OqZivXAN69m6yTT5msjLvjSlbGaZrcAfjvy1TCpOvQ7QirjMATGHIgkKRnDmPWirSMPEim5PcAVwLXaJCU2kKNLvRSBKZT+ywixLGoCRE55+PQRLggdhD6HZeoTNK793sk7Jpz1YB3TchqnIO26PCTv4adt8NLPgY9mwGVqPier9zPQGuOD7x0w0nuYIyTglQOXvcVxMC5vOrZv+az5w3xq6eHedkn7uCpQ/XDGGLEiLF4oEKUZKRLJMrr05pLEWXftA//WrUXCFP02chCuOGIxUqNUqVGKd2KYZXITzwdUkQDvzw3qFpLU/llHDHbmcgvd0YRMTLlQXO8gJ5ktPq/UDrg5WiEctCkb1spPCn26UD4lpOT1nr4N5qx5h/HRKnKXOpnEDZ0gzk0wleY2XDV8BwUy9WIc+N9YCxA6OOZoUmeHpokWRkPtSkjXs0HP370EAhBZcwvHuLU9JpvzTMpROShg95Ns8549TA0szbjCw9TxNPbNihQoaNeeGP3gZ/Qvvt7AIwWK24trtHm9TjNz4ektTWkaMwmEULglBqfb56mFIJ9vVfOSsqL5RqPH5xSQiuz5KI5xxVCzU+qMuYTgDGsMrmil1upkwXn8nNC9aRhznqeR1pOq/tdcy5FPu09X0I9nuPydkN2Z5kTvd6baShCqnvQnGsqUS2SKh7yPeCUyI2MbGtuqHZCiwxWSYn7pBNaKPZc58prI6wg64eeB1yYeNp3fQUXo4KhrFGICdqJxCPfhDs+DtveDFteC6gT+t5b7+fg+Awfe/UWGtJH57aP8TxAqgFe9xXo3cLFD/wp395eYWKmwss+8St+/OjBufePESPGIkA4yR6UR8MMGjNidk9MMIxLBF9rP/BVS2IJz+MWhcNt23zePSEtLDPFkfZtWGambt0pJxDMMThUcWeviG3CMJCoulGOcerloKm9l7Rm7c9N97uo0EFQ9aOUZDuRsX5th3+DsKquRy8K9Wp+OXCMYKEVV9ZhEVbC0425xAKsJz2vL+p863Le84UisyLkNfCKLs+X8EVlHYb3rkvQAh40fXxOCKyDoEDFnJASszYTOTcqvNIvwDAb+lpyerOAKho/HySq00gjVV/gFCW2MTJd5pmhcF5WEEJWFUHTLjC3Lt8s0vJhD1qC2UY/3eAJzQWJiCVU8medAAAgAElEQVSl/1qcZTEiCg6Br3ddhFoT0Lvv+zRM7XI/6yyo503j+JNIKf35i44Hft6e4HrH9ffPMFRfVP/tMOFZoOe8zRU26q9x5r9mVciwTjgnfeONQkzQThSGn4T/fCf0bYOr/rf78b/8/Gl+9Ogh/mr7OrYOtJzEDsZYFEgX4He+Bu2rWfPTt/H9lydZ1p7jDz53D5/46VMLTyaPESPGooCQFulkICRJzk7QQjk+wjMohPB7AGYLiXPbE4aP9I03rnJfb+hvcWX8o/sfzk9zHCKON2n/mE64XD8b/S1ZssmE24f5iCnUbAGTYjYc8p8qj9B56A67wLF2RK1Zs+r1ZTK/rO5xBNGr6EnT0MiOgh6ClQhWQ54VGkGLMGhdz+sCsX98xiUNE4UVAFiHn1LEY472Drdto9R3DiB5Zkg3QhXx3jfq92jVu049ERKBsCok7EScUrpVCUk8p5+s8M6HW0/ncOvp9reCSs0KhY9F9lNv1Z6bbLB0QR04YXkTTavqblOtSRXOJpgzpFNYtVAFOyec2bBmI+pqbg27nlui6i8IrSNYykESfPbIwG0Y3H72e9R53szXj2waIuSxdEpvIC0mS7r6o9fyQtRoPdRfEDEQCCG8UM4FhInOlGfvi36tB/tdrfkjK5pHH44QTPEjJmgnAsUR+NJrIJGCV31WqfcBdzw1zN//1+O89LRefve8ZSe3jzEWD3Kt8IZvQGMv7be9ga9dm+Pa03r56A8e54++dF9kEdcYMWKcfFgOiYk0juUs4W112guGOOr7Sv/qsiX9JlWUYSPxy5p5dYogFSSPNg51nl9XscLzoGleE7dYrDIvmkd+61c8lNI1/pxCtlFoHFcCBOONKyO/d1a29TnQj6PnqwRDO8MIm0J9zVk6A2JdOpHTidZIy+Y52q9/JClVfapscV9o27nCr3YMT7FzeMreVp2/VHmUzkN3kKhNM2NL6Eehkmykd8kKzNqMHTaqtzsdIvxz1W6rGSkElnsOhjvOZaR5A08P1a9HNheixEVmcj3M5GzSLgQ7hqd4eN9YaLsg9PO1UNJYta/TxqWnMdWwNHIbJydwPoRFqaUKtx9J0+DMFd0kTWP22l/2Ao1Dig2rVJfQhcQsIq4l/ZTqQjNOL2eDc33MN9Q36kp2HisCGVp8dp4jofIj84D+7At2zzCEe41KBFL4c/FmQzFge4UEjHwELaB4ehQrFTFBO96oVeDW34WRXfDqL0CTcjnvHyvy7i/dx/KOPP/nFZtiSf0YfuQ74Y3fhEwzmS/fwMcuTfO+q9fy3Yf2c/2/3MnuIwuTFY4RI8YJgqy/9hw2zr0f7ShPUdBA9xVPDho0Ei3kMbg+H9FAAGYdWX7LSNqeo3B7jgct4ZMv8+egCSx0Z5Mhq3b+nEAayUAhZSVesLJDJ25e2/mIFABTV/+rO7yo/tnvIkIc1/c0YggRIiWre5q94+pEdxYRCYnhm7qgnSyBStUKKSTCPIil5gmYzoWFKXQJ/FK6zX3d15zlwtUdCALzh7qOdPlyx3iNMsQryUbvWKYdoqeN7+H9zy1/uu3w3b73QXI0l5dHh29xY46lkQ29jb73k/lBADIJk3r5j+UAQXMKhY82h3UF3Bw0+x4eaMlhJpJUatacoa4hKXpZZXl7/YUOx3scLPMhmUPoZg6bNCqdcKIQvZgC0dePc4h0aRgppW+ugoIhC4HuwQx50ISftEkE6YRJch4e8fHAQkbwvtefyemSWlxY2prDEEKpOC4wXDMmaMcTUsL3/hx2/Bxe+nFYeh4AU6Uqb/ncPcxUanzy9WfEeWcxotHUD2/8TzCTiM+/nLduEnzmTWeyZ2Sa6z5xB//9zPwLusaIEePEQGC5OVqAf3XWLVqqfnr1RdWSLXkfbC0MNzvf96lTy0xtIeqEzHkhkjOZTv83xhyryBHiJ1EetCBBAxVW5DYjBDUzS3s+FZn7JYSgOacTE72dMOajEOgQ3VK6zVdwu8U+Tj1j0Gpe5ntvaCTWL9hikE5oinjdl3rHDhBfM8KTUS9vaW4pedUJFd4Yblcn+NM5Lx+pLZ+mKZvCkhKz5g9llPjDZRvsAuOh/ElgtHmddizVV8N3zfr7FNVGFFobUpG5TTUzWH5oAQRNJ9Rz2Mmumqi3M6DIZ1Teo0BoNbAEhzrPZ7j9LPb2XcVUfhkHOy+M7I9j0AsBmCk6CxkKE0/PNgpWd/nJWH5yJ60N9Ym8k3MamRf7HBwDtYhJDJ8fD87s6M9DnTzVpL1I5aqPHBt64hxjuP0s1ayqXm0fQ4AwfIsK8/WmQTgEvRghIpJKGJhC2OVIFuZFiwna8cSvb4Z7/g3O/x+w9XcAtTL1ji/+hkf3T3DT605nZWf9lY8YMWhboTxptTJ89jou6S7zzXeeT0suyev/9S4+f+fOOC8tRoxFhNYj9/ver+vxVuMdY8GTZVD/j7RsqtOad29nEiYFowzFUbsNPywpKWXaaWtIOQoiEe2pvQZacyEpcFF3BdkLiwwaeY7Mvm5MOyv8OvnSDbHpXD+93d0YhrDFDsLS2ICSQwdkfedXCLpN31nQ6l3ZynHlVLOPWa1wPHVBY9DZJO8PEUylkrTapM4nhiEM2vPq873926klcpRTKqdcItBlOJKBYkkzlZo7j0EEyV19RAudgHC9cDpZ06/Coi1X78CS0p/T5cWhAZ5HZqphKQiTsab1lJNNSCFoyaUwhHA9TiFvzzz4wJYlzQy2NcyVQjf/BiPgiFMEkUslGLA9HlHQP9e9m4bhJyyVZJNt/Ctjv5rye+RATaelr7WYSRoz3vkejCi/IQEzcJ+myiORfY3qZ7AtZzTRYZveWKM8dG7+qd7mLKTKI6PRzwW1KLDw8+k8J+rBOYRDVJUHzX/v6r2eqz0d1rzq42m30AKFgGKCdrzw5I/g+38Ba7bD5R8E1AX6V994mJ8/McSHX7aRS9d2zt5GjBgAnevgDV+HmVH43HUsz07zjXeez8WrO3j/N3/L+77+kCtPHSNGjMWBcrIJCBgh6Ub29m933ztGaCXZ6AtBc6CvuK7pLmDuun3WY04WlmMaglKqbVaRiEzSDNlCplnP2FBeNxGRWzc2XaGY6fILZoQKVfvD3hAGg53NkTlNpXS7u7sXzhht0EVB/15vf7phCYMbz2XtaefU2VNwpGVLuL2AJyWb8lbMg3w2lwrko9ir6yr0z1aybMmFvBaWlDTYYglOnx2P3lz1t9x8v4AaXcr0K2kG29J7MNa03tdmpWb58pecaTSEItdOSKpjjE8WBhnqugAQrOjIYxgw1rQmsr96WFxUuCoo8RXlXYoab32TtZxqjvy8KZukr9lvdCdMwxVVcfKRmrJJ1vc00lnIzErQRls2Mda03ufxNlBjO9x6OkPdF86LOAqhOYtQnhx9t8gC9kLMy+t1qPN8DnZdAnieeWfBwD8e9X/NDBNWffqjjugK6OjhgoHzk9O9UXaDiTrdTxqG73pNJOa3OJGeQ07VWTxy8sUMoRdht59tos6zKoBQGPo8vHyWJVVpByO1YMGTmKAdDxx6DL72e9C5AV5xs3vGb/zJU3zlnt2867KVvPasgZPcyRinFHq3wutuhbG98PmX02hN8Ok3buOPLl3Jl+/ezes+fReHJqIlq2PEiHHiUU16q85u2IzrEZHavzDYUaCaLIS8WjOZDgA29zersKuyFwpXz06rZdvIlIZonHgy9J3jjRLav1579VeDXZn9gLdroqRk9XUPWmM2bR9L99gEjpVIhozg0Cq+CL0I9TkIQwiqZg6JZ+we6jyfWiKLbF+NERHG6bRYbOijaItqCLc9b/ukYUCmSdOY8/pyxrJWUgnDX6Dctr4tQ83H8vY8XY3RIWCVmkXSEJiGwWjzBmqJLOt7G+dcoXfzxzR1T0ArFu197jOehdpHOS3U93qIpkTS35Jj02lnuiRieuW1jLSe5noBkiEDOiK0MXC69NyvIKEFT4wjuK0XdhZ9/lXuUvR3hUyCngiviGuw213tLKRh/XXQd3pkO6CMfctMM1kY9AlECDuETRpJqqmmOnuL0DtnjFH3sqmJWfj200RBmrNJBiOUVyupZqrJBru/Gfb2b3efJTrmnYMWsZmnAKuFKQbySdu0sh0t+RTt+bSv3IGONd0F3zVayNYP2/Tli9mHryeI4/TOadsQBqNFLx9PCtM3DzpZW9vd6C6WpAbPZ6Rlo6/tKK91UPioMZvEEHYOaEzQTjImD8GXXg2JDLz2S5BWJ+tfb3+Gf/jhE7zi9D7++MrVJ7mTMU5JLD0XXvvvMPwEfPEGjMokf/LiNdz0uq08sm+ca2+8gwd2L7DOTIwYMY4LhKzRHDAyhOk3ah1Hxbpetbptta91DXoQ1BI5itmeBQX+RJEQrQdqGyFC4WdGYpb93OV+vW6TR8R0b5Urne3zoAVGIMyQB20yP2iHA+L2UbUvqNnHcnaZTVEwUZu2VeHU+4rtWbGs+UtKyKalsPJyvwdNAGktXFX7qiOfpbbmJRzqvCDUluOd8NlygdDF0XQvFa1/gx0FcskEydnOCZCoKsJuWBVfKGgmadKYSfjOsU4oPIPUT7h1r02muYd012rXm5ZOJpR4hj2xDRn/te20LwwzknHoeV35dIL+Tj9hmMl0cbArPH/+Y0SfwdnFVKL3cQmas5UQYCYhG5ULquBXK9UUPev0a31PI5v6FGErZAKENhjq1+U3/g2h17jTvNJuyF6elZ0FHwkK4qxl2liCLsk5IwpFxCvlkdvbv53xptXBYTDQHSaBDgwhWNbWEM7vs5FJmqgMRm/MrbmUL7/OmeeosPF614Zwv7cJWlCkRwh/iHbvGV7bqhsANBUaCE5YqjQauufHmv0eaX28gjjE8eRhZgy+8ApF0l77ZWheAsBn7tjBh7/zKNds6uZvr98cKzbGOHqsuAxeeQvsux++9FqoFHnJ5l7+4+3nYRqCV37qTr56z+6T3csYMV7wEFaNaq4DujZQzKuICRFIKnfzR4XJdVv6uHjzCo60OqF26jsnnyfiCJGfGnVDFdU+rkESKuAavZ+0vTPbljazub+ZLju3ywspE6SShra987FmgAZ7YSZImMIXliYDw9HNwwM9l9o5T+qTXNKkqzHDYFsDqyLzuCWdhTRt/V6oXdUK1n3yjmMFz0tjL2RbQvk+rtcJZUoOtjVQSCcgkUIkMm7O2DLNqxEkl1GoJpRXwZKSUrrDDRld3+vNT1ANsCkbDIHzDmAKQSGT9J0Dy0hxsOti3/a6zW5JSUrLj0smTcBTsjQMQUch43rQgsIqbmFhfzyr+6pVE35pSCUwVl2ObNfOTyKrcra6wyULdOGG7Zt6tPm1vX9Jb96d63Myv4wD3ZeFyHCov44AiDNXs+T96WqljkpjT1Omrjc7YRpkHZGVwP1Vzve5r6srrlBiYHUaqjphpdp8Br2rzhyt7fbIi048osqRu2OWMuS914+ldDX8fXNEUfRPgzmTQsBUQ3S0WJQIjGkaTOfUvMhkA8s78r78Nxnkq8x+X/lFdhwPmk6y1bOtqzHttimEwYHuS9S2hueBNoQIq+piUQl5TCO8nvaCWBzieLJQKcK/v0aFN77689CvWPhnf7WTD33rEa7a0M3HX7O17upBjBjzxtrt8PJPwc5fwpdfB+Vp1vc28q13XcC2pS386dce5IO3/dYnlRwjxvMVQoh3CCF2CCFmhBD3CiHCkmn+7S+2t5sRQjwjhHhb4Pv3CSHuFkKMCyGGhBDfEkJsrNdeEK25FF2FDIZVZqr3XOhch7SNMxnwoLm5PomMc2zOXhHOTY6y2+rlXswaqmg3FGUcGbMl+CPImpKUabhhenq9s3SLpxCoP3bcsCO7aSeETaQLFNZdGSAddt6UOw53RCBMLCPhGiymabCkJUdbPu3mbwWRMA2aOpe479vyqXDI2OoXU1l1tSsRrx3RPo4Z+szpoSEEbfk0a7obIeE30k9b4hErKyK/h3SeNV0F9+1EYSXD7Wexr3+7HZrmJw9ROHswnLPoIJt2Qkh1Y9QLuxWqcX+hZEtiaOQqYSZACPqas3QVMvQ05yikE66hLwOEwwsZDF9/nYWMz3MhkZBIc+a6Fa6HxDNew0QilTAYaM3R3ZglYRqBsg7QnEu77Trtjdmhor45XHI2tA76+psI2mTpPDRH1zozDcEFK9tZ39NIMdeLSBXoa875ripdAVMQTSrATxSMbFPUJh5clQnPgxYU7FnVVWBVZ75ubl/UvOqPgVLGfz0Zmix/tWsLhYz/vFZr4YGt6WnxLZgIvIWcQtouxG1PtyPG0ZJLuXZxez7NZGE5e/uu9uXF9TRlPEEf/HMXFQbq4KBNtNSG3rOvUZsjKQzfQowwhKtGmUmaLlHVj7m5X41ptNn/s7Cv98rIPEnF8xbumInZwrFArQJf/T149k54xadg5RVIKbn5F0/zgdt+y4vWd3Hj62JyFuMYYvMr4bqb4Omfwheuh5kxWhtSfO73z+LNFwxyy6928vp/vYvhydLcbcWIcYpCCPFq4OPAR4CtwK+A7wkhIpdthRCDwHft7bYC/xu4UQhxvbbZJcA/A+cBlwFV4EdCiPqxTzYyCZPlHXlyKZNyuhXHeBHOj3ZghblMElINvriblnzWNTLX9zSydWW/X4TDRmch7TOGDreq3JmoekPB/IyE4TfeAQw7/GZFe55qly6YIVjf2wi1qj0W9alZUzmvuem9mIMXuLkXugDgVEO/3baA3q0c7LrIbhGMQgdEkMmQQSsEl6/rYtuyNtfY1u3zoN3jq6VkKqOwrSFNOmHa22o7pAuQCufEeGMMS6o7pNrUO2GGyd+Zy1pZ393oht/58maWXUhhlRYaJQSlTIdrchsph7AbjDZvZLj9bHfTYrabg10XYxrC9TaAP+QukUpjCC9rMBk4327Yl3aualJiGp4hqnLMBAnTYElrDtMQGIZg7aazmM71UyoEapK5JELPZXOuf78h7WqQSElnIWOLSdgfWtGFmjsLGTb2KlKbsb1FTjNpm6TXrAiRB2de2lerqKauTdC+yp27QhShydTLI1N5Vb226Eg1bRMr7SIMLoy6Q03kWNcdVnP07Z9W43NIliduEg43DHpjUqZBUzCkWicy9vadhQzVRN6OcNSXHdScWsImUlLL00pmQ21XLYtyqtl3/yUTphbirJCoTNKeT7t5kQnDYNvSVnehZ0VHntNswrNtqS1kIgwOTdrHzzTR15yjJZfycvZSnodaCNtLHQjhPNh1sVocWf1iX9mLhCFY5nrlIp6DhoGfGtnXcMQz0zISPo+lNFKRBC2KmqVMg60r+iO+0foy67cx5oZVg/98BzzxPdj+d7DxemqW5IO3/ZaPfPcxtm/u4abXnR6TsxjHHltfDzf8G+z5NXz2Wpg+QsI0eP9L1vOPrz6N+3ePcu2Nv+ShPWMnu6cxYhwv/DFwi5Ty01LKR6WU7wL2A2+vs/3bgH1SynfZ238a+CzwJ84GUsoXSyk/I6V8WEr5EPAGoAM4f67OOORIminGmta64WGuMWWvCjtGYWH52bDm6kAjpvuDnk6YdLc1Q89poWMJIXxG00yux+5D+LfmcNtWhjrOwTIzgKNa5jcbRE6toLc0pDh7uX81vTmXdg3npO1Fc+pBuTLttqXW6Au9E/pXmFG/g7phJYQbZqfX08qnExQyXgiYb8U7wNBynStdiX0RDLkKH93/vXOeHG9Qvt01WIWdh1ez2YXrxek/E6Wu528rnRDk0gk3fNIJdUMISKShMVxY2vFsipy3FjCVXwr5LpbY4go1M0M1mSdhCCXnDgS9I4aZUETLIVumAQjlEYgwIEebNzBRWEll4ELWLulkSUtOecIiVv0T6QwjradRI9qDpouHVJOKcAQjajNuyKIkn06wvrdJUyyNChGzX9gCGe2BvCtnAURKGQpL9Ryx9qtECnpOY7CjQGtDir6WbNjzFEHMIaw8WU23+PsXgMQLYy62rKEhnXAl/ke1os5OfbjqElUr1yGwuZTJ3v7t6D45h1SNNm+ETEC5snW5+guO3caqzjztDSkmCoPk0wlNTAbMTJ2SE4As9NK1dB2b+5vtYt0KlkiGjiGi3syzFJDfm+k8NML5haJthfvaSGY40HtFaJuas1+6QC3hLcKYhvAXqrbH6zyTTcMAIVRo5uDF7slV15jwDatmZkNlM/TQX0c0JbgwVMx0sbm/GXNVuN86YtbwXGDV4Btvg4duhcveD2f+AcVyjbd94V4+e+cu/vCi5dz4mq2+myBGjGOKjdfDa/4dDj0Kn7kGxvcB8PKt/fzH29XD/oZP/oqv/2buYq4xYpxKEEKkgDOA/wp89V8o71cUzo3Y/gfANiFEhK41AAXUb+XsBYdAiQwArY15VnQ2usns5UI/UphU84rMSGDb0lbW9kSt1As7L0ozQucoIq0rh4moUEVhUk630dqQ4vQBuz5X0KoUAloG7R7Alv5mNvU1cdHqDvWJZrQuacm5hsuKNZvtManjtuR0pUKt9pGUXLiqgzXdBZfIXrGuiy1aOOCa7gKDdihT2Oj11vv9uTUKzTYxPG91FwOttkEWyomZxfgHDGl7b2xSZaZz7O97kTYci8G2BtrzabKOodroebGisLq7ib7Odu/YzvmJOE/9LcqgS6Tt/ltqztMJgzVdBZ/HwzBUPmFfc5aLV3VwyWrPS2qY/hDHvpYshhBcvLqDzVvPtY9vuh6JqfwyxpvWYOS7yGUyyrshDJcQ6XBCSmWAFLpqd8kkl6zupDGbpJrMM9RxrlIk1Ca6y6lDphvuDjluUl6FllyE8EdlWm2STXLhKk+QwrmeLClDOUnFSnSo/+b+Zpa35zECCx2qoQqdhbSvlt4FK9td75DTa8s2/OsR/yNTJU+sptAHm25gSUuO0wdaqAitTp97adjXVJDQOB5P7aNSph0aAmGufaf7VCj1a7uUbidhGOQGz+S8bWfS1ZixxWSSbOhr4sJNq8g1tnO4basamya8IgTQPEDKNDhjQMuLbNngy6XTJ8MQikxONK5kXujfBnhCNU5eZhT7FTmvZIDRvV4/rIZouzthGO71IqTFlgG1GLKsvYH1PY1kDHXNj7ZsgnwHph2WbtjEzcFw+1mU060kDIODnRe6EQz6Ngd6LoN0wS5o7Z29qfxS2HSDWiyYBTFzOFrUqvCNt3rk7KI/Yd9okVfffCc/evQgH7p2A//PNesiw01ixDimWP1ieP3XYGw33Hwp7P0NABv7mrjtXRewZUkzf3zrA7zv6w9SLMf10mI8b9AOmMDBwOcHge7w5mB/HrV9wm4vCh8H7gfujPpSCPGHQoh7hBD3DI8pA9IQ6v5zFueq6Rb29V0VXvGOIlOpBsr5Pobbt0WouEVjqFPjo3ab441htWBTCLItynNz2rIuLlkTzHfzKucmTIN0wlTGq2GGvQq2EdnRpAhVqjLm7ut2RVpkk6YKsTMMmrJJX0hQQzrhyru35TN05DNutMls+Vf676oQgo29TSzvCIuFNDVkaM+nXSW9OT1odt6NSNgELfj73bqcXM8qlrU1qP6tvw5sA65edwfbG+gZ1HJVHNITscP6nkYuW9tJNqtCuGR5RhuvdMfh4Iq1XfQ0ZRFImnRCYyZJp+y6UjYBuWZTN5mkSbp3gzIODSPEA5RX0LGwDUhmId/pM/qzKZPN/c2cPtDCucvbuHxdF6YhvBpx6QJNuSSXrukkYRhIYdrEUh2sq5DRzq3XgVWdDZw12AqZRth0A8vbG+hpCpQlyHqGeTqhDOakYbgCHJb0vFEOarN45lhyFgxeZI9XI/MdaxkYWO4RffzXo+MVq2ZbFaGsm78pQq+FEBhC+EQ+3AL2ZpqakdbyMCMWUeq2H3F0bfuZbCfVtS+DthU0aJ7A1V0FulqbSaWSVAYvo5xu41DnBQy3nzXnUWqJBord23yfGUJQSTa64ZnSSHpn2c7/i0TLMgC2LVPnuJrMq/JCvd61N9jeQC5p+vJsdfGVjb1Nbn6YFIZPXMbb3htPunTYV3g+l0pAacK3/eaBNjb2NgXy3qBkly0wTUE11ehGMGxZGvgZWf1ixga3Y9aK7kez1fPTERO0o0GtCt/4Q3joq3D5B+CiP+FXTw3zkht/yTNDU9z8hm387nnLTnYvY7yQMHgRvPm/1IrMZ66Gh78OqFCQL/zB2bz9khV8+e7dXHvTL3n8wMQcjcWIEQNACPEPwAXA9VLKyNUNKeXNUsptUspt7e32j3MgP8RJqA9FU0RZ9UIw3X0mlVSzlo8VjJ9rVAXsUZ42qakQzkZsJKhcnLXb6enuiVACdFuB5ZdC2woVYhSRK+aIFCRmUY1szCbZ0Nuk+pSMrn9EoYctS5qVOIqvdlrwgKIuXc0kTYzW5ZDzpwmaZoLzV7bTlHPCFL3vnAR/vS3PgxYekyFQZKzPk+F2PKZAZJ5gnZG40HMI+1uUoEUhk1QhkIBVU4TRIR3q+tHaE9GvTUOQS6ocMjcMcrZ8PxuGEOBc5sL2GAxe5AubA2UoN6QTdDZmyKcTbN/Uw9krbI9WMuwZqjs1Wgd6GtO+emVCCDcUMl1oU+JYEQa+YQhPOVKCaFnKynOuc79300ui7ovmAa90gkb+SGZhsL7WUEMqQUsuxaalnTBwDpVMdHrqht5Grxh14PA+MRHXNWz6wvXCfuJAO3MIT2SS/omvRRGDtpXu+XWayzd3UEk1eSG3sxxnlSZ2A2BsvJ5zX/RquhozXoSje6xVzIWCXqC7bYVbqgpULun63iaf59AJMayZKTJJk5RpqHMujIgFKMimEojVyisuZM273h3YRNFtP5m0r8NoT6xeesE0BH2t3nyk3MUmfPXrfNERsyAmaAtFeRpufQM8/B9wxYeQF7yHm3/xNK//t7tobUjxzT86nyvXRxfMixHjuKJrA/zBT6BniyqU/tOPgFUjaRr8+VVr+dzvn8XIdIVrb/olX2gFKNgAACAASURBVLxrlyfxHSPGqYlhoAYEH7hdwIE6+xyos33Vbs+FEOIfgdcCl0kpn5lXjxxDpnWF7+NSVf04h1Z0zXoEKdSw/222GZochUL/fexTP4yC4xmxceayVs5xcs70Z0JDm1rBFiKSsDg5Q4btbfJConTtds2oqVdfqncriXXbMZKpEMkIHNF9ZkXai/1nqDIkOkI5aN6OtQh1xZGWzZSTTT4yuaytgYOdFzLaeVZoex2h/s7j+aqH1q3s0Axdu98pwxZ2aPT6etZgKxesDDp7AzloGpU90nqayqVJhotkB8MUDQOvGPo8V/lBGfBevl+YVhhC1FEz1EMcw/PV1pBmXXcj7Zuv8l2zoAiOtDMVnbxLS0poaKe53bvFexvtOY4I1wTUvCw9T/3NNkbttWEILlrd4ebClVpsb3XW7yFXKoABOfpsMzS0+35/HQLuKLOWV12j9nFDG529g8Wr7de5Vlj7klCf04E6ejUr4prUQnSdtvtbsly3pc/tV/B2c0Q9QOXlDbef7QnZBEIB/R0qQMcadT066DtdLQZpOH2gJeIa92OqYYmvb5WOTep5BWzsbeTqjT3ugtjpAy00ZpOcvrSNVEu/G8KcTxK+7oICMYYjmhJ9/SQM4c6HQPieOVfYXMAQYFold36riTqLVcG257VVDIXpI/Cl18DuX8M1f8fw+jfyZ5+9h588doirN3bz0VeeNovEaYwYJwD5Dvjd2+Db74Gf/y3suF0pizYPcOGqDr73Py7kj2+9n7/8xsPc8dQwH3n5JpqjYv1jxFjkkFKWhRD3AlcCX9W+uhL4jzq73Qm8PPDZlcA9UnqyZUKIjwOvBi6VUj42/14JlRcaMFBWdhb47b4x1wBzbQIjmqA12IIS6WS91X/hGtDOKu25y9sYniwjbAd5VBiNFWEE9zbrhm+d5f4oY90V1FDfbT3jXMSBB5jRjuEaoS3L6udbGIZSsgwcJ1T8VyiCNp3tZWbwTBi+Pbo93z4BYhnpsPQ+LGU6GMp0+Gp5LWnNsfNwI5W63sZ5QB9LQ7Th6VeFtIVFTLhidRe5lAklZezlOgbJ5WZfgTeKR8A0SFQnlHc1H11AONKD5nV61mOE4J47r9GKJUmgFCzLtgfCz8+0DnSs9be38nJ46scqHC9KuAIVxpsr7bBV/aS63uxts0mTYqWG6XhFR3ZCT7jGGhAp2AJA71YmRlX+9mzOqlquk/3922lMJynNVCK3ca+zlcpDZj20X/tO/Z9JmlyyupN8JgG7uhCMqyUojahZA+dwqDIR2LE5koADnLG0hUf2jVOs1KIXZSMWX5ytnPDQhCnUEpaNXMq/TylTh0yFHlsCujepslQOAt5ZUPecD6uuVPsMPxEWDRGCi1Z1KBGepAn77sM0DMyE/x5WbdpivdUSG3ub7JBebU4SEfdV8xKYGrKvMdXvhGng1JxuzCbd3ERD4JtPPVx7JtNBYXoPUkIhmPNYBzGbmC/G9sDnXwEjO+CVt/CzxHn8ycduZ3ymwgdeup43nbdsVjdwjBgnDIk0XPcJWHYhfPdP4V/Oh+1/D5tfRUchzWd/7yxuvv0Z/u4Hj/PrHSN8+GUbuWpjvZSdGDEWNf4B+LwQ4tfAHSiVxl7gkwBCiM8BSCnfaG//SeCPhBAfAz6FUmZ8E8pThr3PJ1DKjS8DRoQQzs0xKaWcnLNHEb8DKzvzrOzMMzIVyOOKUChzti9kknS7OTgRuSi2IbCpv5FN63oxDUFnY4bDj9vGXIRRW63N4dWpl68TER432rKRprHH3DEkEwlFtjQjsJjrgUage55l5Jw+d6yFoSAvFrQ0pHh20qClpRUOGyoEqm1lXWn2+rF184fru1jo77uzkj7P/Xy5Uw5xt6pevpCdmxWJaE0JJvNh43c2hEjxQuDsq53/pCGQSFIJg+ClD0DKDl/r3RoWvNBDDiP6JSUUG/o43L6MDe3NlPIpenO41+plazuVGuKj9g51lBlnRdsKJhuzc3pDHc/URMm7Dl+0vtvtJ4S5Ss2SDHWci2WkfNeWE47L4IVUixV4/JCrkAlAYx+V1AH/mNL+MEMd/S05kqbBfz9zOKCwakMjFMFT6Iwrl0pAbTbvdgRaBqkZE1AhXIJtAd5ZQHm1Mk1Q8OyUrOYdbGlY4CKzkfCURJ2Fpu5NyrsXROtyaBrAKFk4BA3gxRu6GZ+pkDQNarZ31pm/jnyasaJH1A0hGGtaS2F6D6s7C6RWzO4ddBATtPlg72/gy78D5UmKr/4qf/tYB7f86m5Wd+X5wh+c5Ut6jhFjUUAI2PJaWHoufP2t8PW3wCPfhBd9GKN1kLddvIILV7Xzp199kLd94V5esrmHD127gbb8/GKjY8RYDJBSfkUI0Qb8FdADPAxcI6XcZW8yENh+hxDiGuAfUVL8+4B3Syl1j9s77P9/HDjch4APPpf+OuIWroFTJ8RRCKGRM/yr3Im0yiOzjRwTfBVnddNpXXcjjx4Yd9+X51u8PmgQRxCdcr6PA7leb9sI4QcpTBV6OF84bQTC2ZzvmrIpLurrgkwSNr5i/u3aqFmSYrabzMxB1i/zh0j5DuWr2eUUpp7fMVzDr+8MOPwUNHTAjFbqpA4p9xm9DrmbKwQ2cJ76mrPsHS3awgmSZK6JrFm/48EcxKDAxlFBIzPnrWzn2b0l0tPe9VPJ90KrHe5a6FKeMp2M6Sh0w0R0tHIhnaCzkGFdTwHTECqfrzjq3iuhAtRR3pF5QNhOltkKIjshzC25JEemyqzqLLhlFepRO0tKu1ZifTiXhFOqQS/nYBoCqjZBS/i9Z1uWNHtlHYCuxgzXbamjNlrnegToH1jB3mkjRMjmpUzefwaVfBF2HomYg+d+nW0daKZ2uCnc1mxCJA705+lsIjIOzARC+D2jmaTp1eNzAw9UG0vbGnzbGkLVSBvquojTN/UqT988EBO0ufDAl+G2d0O+i/uv+BLv+s8yu4/s5E3nLeMvrl6r1fOIEWMRomUZvOk7cOeN8POPwifOgnPeARe+lw29TXzzj87nkz97mn/6yZP84okh3vuiNfzO2QPhH7cYMRYppJT/jCosHfXdJRGf/Rw4Pby1+/1xC4VoyibZ3N9M7+DVYJXm7V0hr6XNrXup+t8uHB0UJPGYhMDq3coy8wkyHXmeHpqc24NWz5yMWPG+akO3f2unFpXe2kLTXJ3j2GNa2ZFnMJiLstDVdw01SzLd0M90rpeN7W11t9NPi2e+zX2urtnU43mhkhnNc6jt2xdNWP0EzVBepXxY5CAaqpc9Gy+hBwm5NqjM8KKgVyqAJa05pss1HrNJ/HOYWij0APf5DOSmbJJNy5fAM0/BuArpq7Ssgj6tyHU9cgYwcG5dz5dhCM5dETG+CG8v4Kk1LhCGENQUQ6sLx9O0uqvgFmB2u2P/HyQ56YRBqTr7golj8GeLiqSmyqPuPZVNmqEwYwdBgjArNILmhGA7whvdmy+PlMNtSM2POtSdMrfUxNE/apOGIBllf9e5v0JINSjve3nS36c6mG2BJpRnuPxSX8ip80yopRtn9XaGjjnvLV9oqFXhB38J33gr1b5tfLjvE7zsP8ZIGAa3vvVcPnjthpicxTg1YCbggvfAu+5V+TF3fAxuPAPu+DjJyiTvunwV3333hWzqb+IDt/2W7f/0S3719PDc7caIEWPBGGxvIN3UDS1L597YgWEqr4ou0+8YFAW/CaUTCdm6nPatL2WwXRlsVWsOD1q91WRdbMM+bsJRSwvuqxk6UTlvsyJA0JpzKc+rX8cYXQjanFAoYbjGqC+yMMJgXIgHLWmGvQ0+tC4PeXJmMop8h/ZrWzEPYy6wT/MSpUyYagiHDNZBIeOdW9/4ZyNOUUjlVAhmQEkTw4SVV9BYUJFGnc3hcgh1YZjR3tRICG+fKKSPLtJpPufdmbZExMYDrTlWduZZ0+0/l+fNIYLha18T2MkkTdZ2NyphH+eemKNO4qzQ9l3RkWdzf7OvvEDkLgssHxV6DDj3cHtESOFCcbQkb83V0L5Kd3/NcZj63ztNuPdPQ5uXV6s1vdCexh60KIzvg6//Iey8nd2r3sBrd72UfRMTvPWi5bznytUxMYtxaqKxB17+STjzLfDjD8IP/xf84u/hzDez6uy38YU3n80PfnuQD3/nEV736bu4cFU7733RGl8h2RgxYpwkrLvW/94wYHVY3U6jZ+6rxCxhbj7k2mB8r8+4AJQq5SE7mWfN1f4k/8DxpNaDBf9WNg/A8JOKdOba/WTGrR929L+/hiFIGAZVy4o0uHqbM+wZKUYKDT6nHPN6+266gcO1vUffroPnoMird80UQuUuV2egafYC3AtFQ1IVZyc/PwW7o0eduT7q8yfm3L1+iQV1zW3oDRekb8wk2b6ph2qUsqINx5PVvPo8ug/+wl0scMmeXhJhoWjsg6r/PjYM4S7m1IfqQyZpMlNRx48aH3hzNt2yFvo0b7Bh1M+nnDeOkQq1s/hkzE6HZuOkuZTJQGsushaj2vforr2YoAXx2Hfgm+/Eqpa4pePP+OuHtrCqM8PX33BabKjGeH6g/wz43W/B3nvhjo/DL/8RfvVPiNVXcdXWN3DJ/7yUz9+1l3/5+dO87BN3cMW6Lt512UpOi6//GDFOHqKMwHSEQWCviAtpuaZqar4hy+2rFDnKBLwNukJcMhvt1Yjwvp01OHuOTQjZllmEMGxj9Ll4C1DiEU7OkI50wmTrkhbWdDf6QrytqAX2TPMxIzCdhQyV+eYGBtFgqzMGajctBLrHVQhUXtjxgCPkMochfNSIyIE8FpiPs2jLQDOP7Z9YsCJywjRIzHI5pxMm12zqISkrMBoxb8/Fq7z03IXvo+HytZ3uTK/sjCYmzrVVbF4FrfPz6C4czzEivWuDWghq9tKVl7Y1hJ6Zs5EsIQRbB+p7nJ19550DbCMmaA7KU/Bf74d7/o2D+XW8ceIt7C718RdXr+L3zx+cX1JkjBinEvrOgFd9Dg4/Dfd+RuVbPvZtMvku3rLhFfzOa7fzmV1L+OTtu/jRJw6ybWkLb75gkBdt6J6filOMGDFOOIQtGGDUSq7XZ97eHyHC5Gy+sAlaPpOkgzQbepuObbRJtaT+P0qxBwfZlOkTUHB4ZWtDCsMQoVI5nYU0/S1Z1vVo87LqCo4OYfJw7oq2o69Jmc4/Z0+E/iifN5E/GuTaYWro+BG0bIsqhTSL6MXRwDGuZ7uDGjPJhS9GzBNJ0wCrjliM9dzDfucNR7DGDhWdT566qwp5PPpzrOq4GmZIvTHKGeN7hBZ6FnaIozSXYoIG8NSPkN9+D2L0Wb5gXMuHhm/gRZuXcMv2db7K9jFiPC/RtgJe9GG4/APw5H/BfV+Ee/4/cnf9C+9s6OQtW67i59ZWPvokvP2LI/Q1Z7n+9D5uOGMJA23HO1wlRowYC4JNsCwzFTIqO46rSqudq2UYC8qvmTdqtopaIrrekw/NS+dttDakE5y5rJXOQvTcGIbgjKXHx/h2cFJL9NiHLmQSC84tWhCWngeV6eckDDEruk9T5z24wJDKq/y4o8SiqJ5kGGocHav9n7vJTSeAoGWaVPhrnTp+UXB9mseDoWUaYQxfUfnjCYeo7+27hm3L+he0r3N/97csjE+8sAna9BGs7/8FxoNfYbfRx3tL/wtr4Fz+/eq1nLns+D6QY8RYdDCTsHa7+itNKLL2yG2kHvk6V5Y/xxVGgpH+rfyksoGv/mwJn/rJCrYMdvOS03p58YYuOgvzMJxixIhxfFHoZbj9LEppvyH10s29x9fYdIjTAlTKFoSezcp7lp9HzcYlZy6oaX+x7hcmUuZxzq03k2BG5yodExhGWKAEYM1Vz61Zt0j0SUbUOAbOgSM7IHuC0g+OMvxVHo/Z61gLDZ3zFsN5rnBDHI/iIerkDmaTC6NcL0yCVi1TuevTWD/7W8zKJDdVX8b3Wl7Pe67fxJXru+KC0zFipAtK8XHj9arWyu67EE/9iNanfswNw7dwQwpqIskjh1Zy+7dX8effWoPRdzpnb1zDRas7WNNViO+jGDFOAhKmoJRRuUk+hcLjHZbcvEQZ4fnjlMOUaoC+utURTg2cdCs/jIpdeiGdjNM4IuGE6R1lmuBxRaph/kXgTwaOT1qg3bY4YeQMnlummyOmstBUqRcWQZOS/Xd9jfRPP0hraQ+31zby1ba3c80VV/BH67uO/w9YjBinIhIpGLxQ/V35IRXnv/suzF13sHHXnWzc/13eYd0Gh2Dvj9t4+IeD/DS5CrN/KwNrz+L0DWvpjEOFY8Q4IdDzvuZTu+uYojAP71aMRQUn/22+ta1eaPA8aIuQXS9ynPDnz3HEc+EHDXZea0edMOp6eEHckc8OT/Lk7V9h4LefZFX1CZ60+vhi70c44/JX8fGV7fFKf4wYC0GuVUltr7laPX7LU7D3N7D/flp33cN5e+7jxVP3wLNfgmdh/AdZHjH7mSysINm1ho7BTfSs3ILZOqhqtMWIEeOYQRfwScfiVosDi9jG6GvOUqpaLFtIceMXEJL2/XRc8qheIHihT93y9gZ6mjLkFrgI8ryzjqSU7B0tcv/uUR7aeQjxyH/y8umvcrmxh32im5+veT/rr3k772qKH0YxYhwTpBpcD1v2PPuzmTGsfQ+w/6n7GX32YczDT7Bs7Nd0jn0fngB+AFVMJjJ91JqXketeRa57tSrk2rpcSd4mjq0aV4wYLzTEUSGLDYvPVBVCsKJO/aYYcPrSFnYenqKlIf49WigcRdTnS45nT1N2wUIfoO6xhZIzOAUImpSSSk1SrlmUq+qvVK0xOl3hyHSZI5NlDozPsHN4il2Hp3lmeJL81C5ea/6Et5q/oFVMMFJYwdD5N9F79mvpjVfsY8Q4/sg0YSy/iL7lF+FUC5JS8uz+Azz96H0M73yY2qEnyE/tZtn0syzdfzcIr2imFAa1xn4SbSs80ub8tSzz12WKESOGD+evbHfzHo4Z1ly9SBNxYsQ4fsgkTdZ2H2XpiRc4simTl2zufd6U5TlepRTqYdGylcv//mfsHilSqVnzci1vyE9yffY+LkndwfLqg0hhItdcA9veRMvyy6KLfMaIEeOEQQjBQG8PA709wDUATJWqPLJ/nK/uHmXns7sY2/s4ibEdDIiDLDtykJXju1m2824arEm3HYlANPZB66AibDqJa1mmPHoxYryA0X485PTj++o54PlhoMaIsVA8X8jZycCiJWjXbeljqlwlZRrqL6H9mQataUn/1MN0HbmHwt5fYO69GyaAzvVwzl8htr4BEScsx4ixqOHUIFJlLZYDl7qk7aE9Y/x87xgP7R1jeOgAAxxgqTjICvMgG4qHWX7gEN17HyZXGfE3WuhRZK3QAw0dqm5LQwfkOyHbqoq7phogVVD/J9KLOkckRowYpzgK3apWVduKk92TGDFinCJYtATt3Zev8t6UJmD4CTjwMBx8GA48pEQJaiX10Os5DS57P6y/DtpX1W80RowYix5+0qYwU6nx9NAkTxyc4PEDk3zp4ASPH5xgz0SRAtPK4yYOsj4zzLrqEEsPHaTlwC7ytVFS1clZjgYYCVXsMpFRoZOJrPa//ZfI+P+v+1nW34bbrradcZzrDcWIEWNxIZmFja842b2IESPGKYQTT9CmDsPhp6A6A9WS///SuJLwLo7A9DCMPgsju6B4xNs/2QBdG+Cst6iq5gPnnLgifTFixDgpyCRNNvQ2saHXX+h0slR18093Hp7i2cPT/OLwFHtGigxNlijXLNKUaWOcNjFOi5igPVmhLVmhNVmmJVGi2SyRN6s0GBUylElTJl0tkayUSE4dIWmVMK0SidoMRm0GUbX/jjbhP5GxPXh5VW8ulbe9es7/Bc3Lp22TalB1poykUr80kvb7hPpDKqkxq6ZyhWTN/9r5zqp631k17XXg8/5t8Yp/jBgxYsSIcRJw4gna0z+Br/9B/e+FAdkWFYrUvAR6tihFt7YV0LURWgbjfLIYMWIASiVqY18TG/uaQt9JKRmZrnBwfIaD4zMcGi9xYHyGI1NlDhcrPFOsMOb8Tan/S9X5iiBIUlTJUFZ/Qv2fNys0iIr631B/WaNCTlTIigpZSmQpkbOK5GaK5IpFcrJIVh4hI4vqzyqSkdMYJ1vx7aX/FBO0GDFixIgR4yTgxBO0wQvh9V9Xq8iJjMr/SGSUpHa6Uf3FBCxGjBjPEUIIWhtStDakWNczPxWuas2iWKlRLNeYtv+Klar7eqZSo1KTVGsWlZpFuc7rSk1SqVkUaxbj9utKzaJmSWqWpGpJLCnd9zVLUpNQsyxqFtRqNZLWDGmrSNqaIl2bJkuJBDWSokZSVElIi4SokaRGghoIsIQJCCQmUhhIYWBhIoXgvS9eSyGbUSGWwrQ9b85rM/x5Q8fxPUExYsSIESNGjEgIuYDqe0KIIWDX8etOCO3A8Ak83qmEeG6iEc9LNOJ5qY94bqJxrOZlqZTyBcH2hBATwOMnux/HGM/H+yMe06mBeEynBuIxHT3q/j4uiKCdaAgh7pFSbjvZ/ViMiOcmGvG8RCOel/qI5yYa8bwsHM/HOYvHdGogHtOpgXhMpwYWw5jiWMIYMWLEiBEjRowYMWLEWCSICVqMGDFixIgRI0aMGDFiLBIsdoJ288nuwCJGPDfRiOclGvG81Ec8N9GI52XheD7OWTymUwPxmE4NxGM6NXDSx7Soc9BixIgRI0aMGDFixIgR44WExe5BixEjRowYMWLEiBEjRowXDGKCFiNGjBgxYsSIESNGjBiLBMeNoAkh3iGE2CGEmBFC3CuEuHCO7S+2t5sRQjwjhHhb4PuLhBC3CSH2CiGkEOJNEW3cYn+n//33MR7ac8ZxmJv3CSHuFkKMCyGGhBDfEkJsDGwjhBAfFELsE0IUhRA/E0JsOB7jO1qcpHlZ9NfMcZiXdwohHrTnZVwIcacQYntgm0V/vcBJm5sX3DUT2PZ99phvCnx+SlwzxwMLne+TiWP1eyGEaBFCfF4IMWb/fV4I0XxiRxNG1PV5qo5HCNEjhPisfZ5mhBCPCCEu1r4/pcYlhDCFEH+j3Ss7hBAfFkIktG0W9ZjEHLboseq/EGKTEOLndht7hRD/SwghTvSYhBBJIcTfCvW7OCWE2C+E+HchxECgjbQQ4kYhxLC93W1CiP7ANgP282bK3u6fhBCpEz2miG0/ZW/zJ4tqTFLKY/4HvBqoAG8B1gE3ApPAQJ3tB4Epe7t19n4V4Hptm2uAjwA3ANPAmyLauQX4IdCt/bUejzEusrn5AfB7wEZgE/AN4IA+duDPgQngenu7W4F9QOFkz8lJnpdFfc0cp3m5DrgaWAmsBv5fe5vNp8r1cpLn5gV3zWjbngPsAB4Abgp8t+ivmcUw3yf7b57PxTnPJfA9+P/ZO/M4Ocoy8X/fnp4zmZkkkzshBBAhGBG5BERB8cTFA3W9FW90Xd1dV11X9yfqKuCt67GirlwKuuqKnILckBBIIPcxOSbJ3GdPH9N31/v7o6q6q6qruqtneqZnkvf7+SQ93VX11vu+9VbV87zP8z4Pu4ALjX+7gDtr3DbX8TkX2wMsAA4BNwPnG/fpZcC6udou4N+BMeAKYC3wRiAE/MdcaRNlZNFq1B9oM+7J3xtlvM0o87Mz3SagHf199w7gNGMsPg7sBoKW/X5mtPPVwNnAI8BWoM7YXgfsMH4/29ivD/ivWlwny35vA54DeoF/dWyraZumawBvAn7h+G0/cK3H/tcD+x2//RLY6LF/zK2z0QWnu6ajTXOlb4zt84EccIXxXQD9wJcs+zQbN/zHa90nteqXuTBmZqJfjH3GzLEwF8ZLrfrmeB4z6C/qg8ArjBeSVQCeE2NmNvT3bPs3mfcFuiIqgZda9rnY+O20GrXDdXzO4fZ8E3iyxPY51y7gLuAmx283mc/TudYmHLJoteoPfAKIAM2Wfb6MrkSImWyTxz5nGPV9ofG9HUgD77HscwKgAa81vr/e+H6CZZ/3AkmgrRZtAk40+nQdcBiLgjYb2lR1F0fDtHcOcL9j0/3ARR6HXeiy/1+Bc4UQ9RVW4WIhxJAQolMI8QshxNIKj582ZrBvWtHdV0PG95PQZ/nz5UgpE8BjJc47Y9SwX0xm5ZiZiX4xXE7eiS6kbTB+ntXjBWraNybH45i5AfiDlPJhlzJm/ZiZDibZ37ONybwvLkQXeqz3xZPolthatdtrfM7V9rwZ2CSE+J3xrNkqhPiUxc1tLrbrCeAVQojTAYQQZwCvBO4xts/FNlmpVv0vBB43jjX5K7AS3fJYa9qMT/OZcQ5Qj73d3cAe7G3aY/xu8leg0Th+RjHcam8D/lNKucdll5q3aTrWoC1GN/sNOn4fRB+4biz32D9olOeX+4D3o7sBfBbdFPuQEKKxgjKmk5nqmx+im2E3Wsowj/N73pmkVv0Cs3vMTFu/GP7tMSAF/DfwFinlDksZ5nF+zzvT1Kpv4DgcM0KIj6K7fX65RBnmcX7Peywwmf6ebUzmfbEcGJbGlDGA8fcQNWh3mfE559pjcDLwSXQ3x9eiX6frgH8wts/Fdl0P3ALsFkJk0F37bpJS/tTYPhfbZKVa9fd6JlvPUROMSanvortk9hg/L0e3wo84dne229mmEeO4WrTpq8CIlPJnHttr3qZg+V3mDlLK2y1fdwghtgBHgDcAf6pNrWYWIcT30M3lF0spc7Wuz2zBq1+O4zGzDzgL3Yz/NuAmIcSlUsqdta3WrKBk3xxvY0YIcRq6u9XFUspMreujqB7HwvviGB6fAWCzlPKLxvfnhBCnoitoP/Y+bFbzDvTJrXejK2dnAT8UQnRJKX9V05opymJYnW5FXx/5xhpXZ9IIIS4FrkIff7OW6bCgmdrjMsfvy9AXPbox4LF/lmLt1TdSyj6gBzh1smVUmWntGyHE94F3Aa+UUh5ylGEe5/e8M0mt+qWIWTZmpq1fpJRpKeUBKeUWQwDYCvyzN9AqvQAAIABJREFUpQzzOL/nnWlq1TdFHAdj5kJ0S9EuIURWCJEFLgE+aXxvZG6MmelgMv09K5ji+2IAWGKNKmf8vZSZb3fJ8QmMGvvNlfaY9KMHYrCyBzCj58216wTwbeA7UsrbpZQ7pJS3AN8DTCV0LrbJSrXq7/VMtp5jRrG4BJ4JXCalHLVsHkD3JHB6Lznb7WyT6YEw0226FFgB9FueGScC1wshTKtgzdtUdQVNSpkGtqBHM7HyaorXcZhs9Nh/81RmxIQQi4FV6A+6mjOdfSOE+CGFl+1ex/5d6IPl1Zb9m4CXlTjvjFHDfiliNo2ZGb6XAuh+0zDLxwvUtG+KOA7GzJ/Ro/2dZfm3Gbjd+DvNHBgz08Ek+7vmVOF9sRF9beaFluMuBOYx8+0uNz47mVvtMXkSPWqeleejW+th7l0ngBb0CQ0rOQqy6Fxsk5Vq1X8j8DLjWBMzQuDh6ah4KYy1yL9DV85eIaV0Kh9b0CPZWtu9Gj34hrVN6xxh6l+NvpRgyzRV3YuforfF+szoA76PvnQBZkObphplxO0fuhk7DXzEaMwP0RdFnmhsvxm42bK/Geb5B8b+HzGOt4a/nm/pyDjw/4y/11i2fwd9oK9F15A3os9sz5owz9PUNz9Bj/jzSuyhv+db9vkCEAauRA/bejuzKAR2LfplLoyZaeqX69BfGGvRBZtr0SMRvX6ujJda9c3xOmZczvEI7mH2Z/WYqUV/z7Z/VOl9gR4qfAeFUOE7qHGYfUvdbONzLrYHOA9dQPwS+vq6txtt+Ie52i70CLg96O7ga4G3AMPAd+dKmygvi065/uju9QPGseuNsiJMX5h9zzahL4X6M3q0w7OxPzOsUSZ/ZlzbVwEvBh7GPST9Q8b2VxllTleY/ZLXyWX/w7iH2a9Zm6ZzEH/SaLCpSb7csu0R4BHH/pcAzxr7dwFXO7Zfih7W0/nvRmN7M3r0lCH0l+UR9IfBCdPVxlnUN279IoFrLPsI4Br0Wf4k8CiwvtZ9Uct+mStjZhr65UajrSmj7X/DCBs7l8ZLLfrmeB0zLuU/QrGCNifGzEz392z7V+656PdaAgvR16NEjH+3Agtq3T6jbrbxOVfbg67IbDPq3Al8GkuY9bnWLvSIoT8wnpsJ9AAo3wSa5kqbKC+LVqX+6BOEjxll9ANfsV77mWoTuiLt9cy4ylJGI3oOyFF0hehOHO9FdIXvLmP7KPAjoLEW18ll/8MUK2g1bZMwTqBQKBQKhUKhUCgUihozHUFCFAqFQqFQKBQKhUIxCZSCplAoFAqFQqFQKBSzBKWgKRQKhUKhUCgUCsUsQSloCoVCoVAoFAqFQjFLUAqaQqFQKBQKhUKhUMwSlIKmUCgUCoVCoVAoFLMEpaApFAqFQqFQKBQKxSxBKWgKhUKhUCgUCoVCMUtQCppCoVAoFAqFQqFQzBKUgqZQKBQKhUKhUCgUswSloCkUCoVCoVAoFArFLEEpaArFJBFCLBBCXCOEOLvWdVEoFAqFYrag3o8KxdRQCppCMXkWAF8B1AtIoVAoFIoC6v2oUEwBpaApFAqFQqFQKBQKxSxBKWgKhQtCiHlCiL1CiKeFEPWW318jhNCEEP8AdBk//0IIIY1/Vxn7CSHEPwsh9gkh0kKIfiHEj4UQbTVojkKhUCgUVUG9HxWK6UcpaAqFC1LKCeBdwIuArwMIIZYBNwN3Ar8ErjR2vxa40Ph3t/HbN4DvAQ8AVwDfAq4C7hZCqPtOoVAoFHMS9X5UKKYfIaWsdR0UilmLEOKfge8ArwX+FXgh8CIp5YgQYi36LOFHpZS/tByzCOgHbpNSXmX5/b3ALcCbpJR/mak2KBQKhUJRbdT7UaGYPtRMhUJRmh8AfwXuAl4DvF9KOVLmmAuABuBWx++3A1ngkmpXUqFQKBSKGUa9HxWKaUIpaApFCaRuYr4FaAS2SSkf9HHYIuOz31FWFhi1bFcoFAqFYk6i3o8KxfShFDSFogRCiOXAD4FngRcJIT7j47Ax43O5o6wg0GHZrlAoFArFnES9HxWK6UMpaAqFB0IIAdwEpIBXobtzXC+EONPYJWV8NjsOfQpIA+90/P4OIAg8Mh31VSgUCoViJlDvR4VielFBQhQKD4QQn0WPLvVKKeWjQogG9JdLI3Au+gtoCNgH/DswAXRJKUeFEN8Evog+u3gPsA74T2ArcImUUpvp9igUCoVCUQ3U+1GhmF6UgqZQuCCEOBvYCHxbSvlly++nobtz3Cyl/IQQ4s3AN4FT0Wf/PiilvNGYXfwn4GrgJHTf+j8BX5RSRma2NQqFQqFQVAf1flQoph+loCkUCoVCoVAoFArFLEGtQVMoFAqFQqFQKBSKWYJS0BQKhUKhUCgUCoVilqAUNIVCoVAoFAqFQqGYJSgFTaFQKBQKhUKhUChmCcFKdl68eLFcu3btNFVFoVAoFMcaW7ZsGZFSLql1PWYC9Y5UKBQKhV9KvR8rUtDWrl3L5s2bq1MrhUKhUBzzCCGO1LoOM4V6RyoUCoXCL6Xej8rFUaFQKBQKhUKhUChmCUpBUygUCoVCoVAoFIpZQkUujgrFnCYRgvGjkJ4AEYCGebBgDTS1o2mSzqEoe/ojHByaYCiaJBTPkNMkASFobQqyeH4Dqxe2cMbKNtavbKe5oa7WLVIoFIry7P8bLFwLi59X65ooFAqFwgdKQVMcuyTDsPceOPAAHNkA0X7X3ULBJWzKPp970mdxv3YumUATi+c3sLClgWCdIJuTxFJZhqMpUlkNgLqAYN2KVs49cRGvOWMZ55+0iGCdMkgrFIpZSHIc+rcqBU2hUCimgQNDUVYtaKnqxL1S0BTHHqMHYcOPYOttkEvB/OWw9mJY8SJYdBIjmQb+uqOP5/YfZXGmj7PFUS4K7uF1PIlWPw/WvZHAuVfBmgtsxUopGYqm2NET5rnuEFu7x7n9maPcuOEwi+Y18Op1y7jy7FWcf9IihBC1abtCoTg2SU9A12Nw0iXQ0FLr2igUvsjkNHKapKlOQC4N9U21rpJCUVXi6Sy7+iJ0hxK84rSlVStXKWiKY4fB3fDo9bD7DqhrgLPeBWe9F1afC0IwFEny00cO8ttNR9HkMl67/kW87Pw1XHByB3VIOPIkge2/04/ffhuceDFc8jldIBICIQTL2ppYdkYTrzpjGQCJdI5HO4e4Z8cAd+/o53ebu1m3oo0PXrSWN561kqZ65QapUCiqwFiXrqSNH4Gl62pdG4XCF4/vHyaazPKmRd0Q7oH1bwU1gak4BskYHlbVQiloirlPMgKPXAeb/ltfV3bxP8NLroZWXYmKpbL8+KED3Lihi0xO8vZzVvOpVz6P1Quts9ACTnqZ/u/134Jnb4Infwg3vwlOeAlc9v90K5yD5oY6Xrd+Ba9bv4JEOscdW3u5ccNhPv/H7Vx3314+9vKTef+FJ9LSoG41hUIxFaTxqYRbhQexYUDC/Mpm8XvHE6SzGictnlf1KkWTWf2PSJ/+mctAsKHq51EUeGjvIAtbGnjxmoXVKzSbhj1/0T2L2ldXr9xjAGE8k2WZ/SpFSY2Kuc3OP8F9/waxITjnA3DZV6BlEaC7JN63c4Cv3rmbgUiSt7x4FZ+57FTWlnsJNbTABZ+Acz4IW2+Fx74LN74BTrlMV9RWnuV6WHNDHe88fw3vOO8Enjo0xn8/epDr7t3LLx/v4pOXnsK7X7JGWdQUCsXkkMbsrFBrXRUedD2qf77wbRUdtvnwGMC0KGgmGRGkXqZ1N8cqK2ipbI4nD4xw7tpFtDXVV7XsuUg0mSWazFZXQUtF9M+RTqWgOTANwrLKGppS0BRzk2QY7vkcbP8drDwb3nUbrDonv7l7LM5/3LGTR/YNs25FGz95z9mcc2KFD6v6JjjvI3DWe+DpX8Dj34UbLoEXXAmv/DJ0nOJ6mBCCC0/p4MJTOth8eIzv3t/J1+7azf882cVX3/gCLlu3bCotVygUxyPm21+5hynmIFmC1GMoaFVmKJIimsyyfzBW+Xteoaga1dXQ1FScYu5x9Cn474thxx/g0n+HDz+QV86klNz29FFe94PHeKZrjP/4uzO481MvndpDu74ZXvpp+Mw2eNm/Qud98OPz4M7PQMgzCTwA565dxG0fu4BbP/wSmurr+PBNm/nYzZvpHU9Mvj4KheI4ZA64OOYyta6BYpZhBszSAoY9QMtW/Rzm3EVgFt8a1aRrZILQRPUVXcXUqLYFTSloirmDlLDp5/DrywEBH7oPLv0C1OkP/sFIkg/d+Axf/NMOXnTCAu7/l0v48MUnVS/8ffMCuOw/4NNb4bwPw3O/gR+dBb97rx7Gv8TdefGpi7nn0y/jC687ncf2D/Oq7z7KzRsPI6t9RysUimMPLadHp4XZa0GbGNEDLEUHal2TuUs2BcOdta5FVckrTdWNn2BDVn31z+wlndXY3jPOhoOjta5KadJx/bl1HKFVOAwf2jtYcrtycVTMDbIpuPuz8Nwt8PzXw5U/h6b2/OYHdg/yuT9sI5nJcc0VZ/D+C9cSmK7ptNZlcPm34aWfgWd+CZt/DXvuhI5TYd3fwelXwMoXQ8CuGDYEA3zi0lO44kUr+Pf/28n/u2MXD+4Z4ttvO5OlbSr0sEKh8GAarA6VsrsvwvL2JhbN81g/FBvSPydGoHX5zFWsiqSzGmMTaZa31+h53LNZz9fZ0gHzOmpThyoTEIIcEs1cQzkNk5IF799ZOnlRRUxlNKtNo8ZbDfbdA/OWwMmX1LomM0alEwX5ADoeKAuaYvYzMQI3XaErZy//PLzzt3nlLJ3V+Nqdu/nozZtZvbCZuz/9Mq566UnTp5xZaV8Nr7oG/mUPXPFDaFsJT/4IfvlK+M7z4Na3woNf12eVB3ZCKgbA6oUt3PTB8/jam17Apq5RXvuDx7hvp5p1VigUHliF2kqF0EoEYi0H40ddN+0fivL4/uES5zFmywNzNxDS011jbOoaJV3lcNm+0XQX0WwuSyw1BaV8Fgnv5midTm+R6XT+7R6Lc8fWXlLZ48sa5El8TJdn/DBR4nlxDCHjIZBaxRa0cigLmmJ2EzoMt1yph+h9+43wgrfkNx0djfOp255le0+Yqy5ayxcvP53GYA2Eg4YWOOcq/V8iBJ1/1RPK9m2Fgw8XBBfQZ5QWrkUsPIn3L1zLa1+9nO9tyfKZWye46uWn87nXnlY9l0yFQnFsIK0C9zQqaAM7YPQA1DXm05T4xnRnEnNXQYuldAVJq5nruX5ttxwOMaBledNZqyZZjqX+yQiMHfKMPjzd5NegTeM5TOVvOgxoXUPjIDXiqVxt5AsHs2JVxPBeWL5+Rk41Ekuxqy/Cy563eGYm3islGabu0EO0hxcSXnBGVYtWCppi9jK4S1fOsgl4/x2w5iX5TXdv7+ff/rgdIeC/33sOr1s/S1xqmhfCi96p/wPIJGBoj65ohg5DqEv/7H4Kdv6BZVLjeuDrzY1s3Hgat++7gL975ydYsOLk2rVBoVDMLqwK2nSG2c8m9c9cqvJjzTrOYQuaSa095ULxJDS1Vqeww09AJg6LT9XzhM4w+b6UGPrn9GkYYhpsaB1H7iUo2gic/uaql60oz9aj40yks8QzOeY3zkKVJaM/M+szkaoXPQtbq1AARzfBb98O9S3wwftgmT4zkczk+M+7d3PrU0c564QF/Ne7XswJi1rKFFZD6pth1dn6PyfZNIS7YXgfDV2Pctau+7kkfAPaz39B9IRX0Prqf7MppQqF4jjFpqBVKoRWIhBPIaGPnD1udZPFbHbtDGj2ayulrMK6qtqaXAKmBc1U0FJRCARh3uKqnSPv4jgNirWU0JAJUVfCeiOlZO9AlBM7WmhpUGJ1NW+gWR+7Vgjb2rNwIkN7c3Vy8SlfKsXs4+hTcOuV0LIYPnx/Xjk7PDLBW366gVufOsrHX34y/3v1hbNbOStHsEHPpXb65fD662n/1+fY847HubHubaSPbob/eQ389h1lQ/krFIpjnKm4OFaCh4Trun5ISnuUNvPvWeGDNTX+umsa1gRPjEK4t8xOTgVtkueaRdegaA1a/zY49MiUytQ0yc7eMMlMzih7SsWVPpfpPpnxTo2TyOToHIzyWOfI9FXkOEWbRvfVquAYfI/sG6pa0UpBU8wujm7Sg2vMXwZX3Q0L1gDwt92DXPHjJ+gPJ/j1VefxxcvXUX8MrtVat+5MLv/0j/nQgl9xffZdZA8+Cj+9ALbcNKteugqFYoqMH80HDirLVKxTFT03TAuaj/MNbIdd/1cISGGuta2yJa1zMEokOTP51ab1CXvoYTi60deuwrhm1V0LN70SbjSZYd9AtOh3M5jxlINsxIbyY20wmuTgcIydvWFj4zQGIDGvQYkcf70hXXmbiUAic0IMsFZyigFrzKJsATiyaX35iEEqm+PObX2MxCbhml0FpuuaHHsSrmLu0v20oZwthavugrYV5DTJd+/fx0du3syJHS3c+amLecXpS2td02lleXsTt37iFWxfexUvm/gWR+ethzs/DXd8Sk83oFAoqoIQ4otCCCmE+LHlNyGEuEYI0SeESAghHhFCvKDqJ+9+Gg78zd++NgmgUmmggv1tC4Y8Tm8y1qV/5oyEuVr1FbRsTmNPf4QNB44Ty4Sj/ycv9828FL/x4Ch7ByJFSorponlkdGLyhSdCeuCtge0A5DS7VaWQqLr6Smh+NGveCtrufn39USk3yFojpeSOrb0cHPY5KVS+QJ/76eOha2SCQ5M6t3EvWM/XeS/svVuP8A2MxzNoUrJ/sEptK0V0sJCTcppRCppidtD9jB4QZN5i+MBd0LaS8XiaD934DP/10AHefs5q/nD1RXPbpbECWpvq+fVV53PBi8/k0oFP89iKD8HWW/U+io/VunoKxZxHCHEB8DFgu2PT54HPAv8InAcMAQ8IIaoUtcGC3/xmFSo9YxNpHtk3lBdkAULxtO27K06J1w9779KVtbwFrXpWBLMWuVoub8tldZe8ZJWCACRC7hNtiRBEBxiMJDFbXrtokpXjObaq0QQjEAMp3ULnzHs2nb2UNwD5GNd11VQQk2HXd31Rri2fYyST0/dzs3I6ycbHGRnq91WuO8V12t4zzo68xdM/mpsFzbRmGq6yM6oWH34c+p7zt296YkoWRKWgKWpP77P6mrN5i3W3xvZV7OoLc8WPn2DDwRG+8Zb1fOttZ9JUP/ejg1VCQzDAd9/+It5/0cm8v+tV/G7NV5A9T8ONfwex4yO/iEIxHQgh2oHfAB8CQpbfBfBPwHVSyj9KKXcCHwBagXdXfKJMsqRrlG+sCpoPgWxHb5hwIkM0mQEpmUhlHS5hXnisQSt3wnCPJcLG3A0W4tq1sUF9pn5gR3VOcuBB2HOn6+8TqSzdoXjp+lRKjZU8873dEJyKuGlqZHoZpjIYEALiYzSM7NY3VyCpZ3Kar9xseYWoGvdxGZ46NModW411ivsfgIMPlT4gdAR2/hHS8dL7obcX/FkZtz30vxx++k7i6Snk4jOZ4vjLT1KUKsacV6pxQBykRiBnTCZoOdh3L/Q8M+nilIKmqC2jB+E3b4emBbpbY/sq/rilhyt/uoFMVvK7j1/Ie15yYhUiWc1NAgHBV644g6svOYUvdJ7Gz1ddjxw7BDderpQ0hWLy3AD8QUr5sOP3k4DlwP3mD1LKBPAYcFHFZ9l7V3khyw82pae8EKLlXcAEVrFlPFFGyJyMBc1ZL6Ou+wejTEwl2bIfsum8VaUaVE3Ak3JSfVgQRqX1o8RpJHv6I3SNTLC1e9x+/hrhDHVvDqn5jVOIbFcwmQGFfgoI4OBD1I/ts53LD/fs6OfZo6HyO5poFVqGDz1aPqGzptkSw+vW09LYLm1sUP+M9hfK87D0Zg0Lmh83TPM+MK1u5StSwTa/aDkY3I00LFC+rMnTPeyjpYMHLQxtZ0X/g/p1ML0jYu7HaJpkfvRQyfKUgqaoHbFhfc2Z1OB9fyLXuoqv37Wbz/7vNl68ZgF3/uPFnL1mYa1rWXOEEHzhdafxL69+Ptd1LuNHK65DjnfDb97mP8iAQqEAQAjxUeB5wJddNpsJFQcdvw9atjnL+5gQYrMQYvPwsMukiZsCUakAU86C1rNFX5NhYBNgKQRqyGTNgB7Stsi+gNcatArqKyXJTI7d/RE2dY36P869KL1WbjJl7xbY8xfo/Ku+li/cM6VzOdGcLnvRCly+9j+gWzYqpBBS3J+LY+94gs7BKNt7xu1rvIZ26Za6WqFp+uSrpf5ySoFuzGPtLo02a5CUFedB6wl5R2YsroL3ZMPi+Y0ALGhpKPw4MawndC7F4E59LWqk9NjaNxDlwJDLu76u3qyc/tm7Bfbfj9DSRbtmDEWnothqk1Z4prJm1mBoDwztpjl2pGwpgul3dQX0nIIlatGcMK6jj7Eu0zHaw3tK7qMUNEVtSMX0PGfRAXj374m1nsRHb97Mr57o4qqL1nLrh1/CktbGWtdy1iCE4NOXncoXXnc639+/hP9Z+RXkwA74/fv0WWSFQlEWIcRpwDeBd0spq+KzJKW8QUp5rpTy3CVLlhQ2VDWgTxnRI9RlU7hyVguaRUg23Zzo36ordM5nh4cFzZfgYzkma5x/igHcSlu0zCAlAIlxPT1LFcm5KUclQq3bSFVnvVoikyNWygqZSbCq524aUg5L0OhBfU3bDGLrraFd+jqdcM+UjSn7BqJ0Dhr9aVrQHEFCdDRXRX4omiTrWMRY0YSDD4IBU0GQlZVtjqdc6Xf43oEIu/rCxjmsOBpsWNQCLtY+u1W9Gni3M5317m/f/WOs+ROyvAXNT5NGY6l8WgbQ85VtPjw2+bFgbVNRtjarBb24cjlNMuwj4qRS0BQzTy4Dv3+/ng/l7b+mt3U9b/vZBh7tHObrb17PNW98AcFjMIR+NfjEpafwT686la93ruH/Vn9Od5/6y6emLgkpFMcHFwKLgV1CiKwQIgtcAnzS+Ns0+SxzHLcMqCw5VhmhqyK8ojim4673flG8BnMZjZTcu6Of4b7Dxo5OHbWCMPvFlcx/mgqizZ1qrAsifZWVaFrQJlGbdFbjob2DFYXot0UHdxPc9t6t5zNzkk27P4NL5bBMxXTF0r0mADx5YIQH9ziNuQUCcT2K3bzYYe/zlGA4miqsecIuPGdymk2gLUdddoJVPXcj4yMF5TAw9XXjewciHB6ZoGskll+DZo5v04ImpZ6awDlO4uksGw+O2t0/mZwH3kA46dkfZn3GJtL8ZVsfD+4ZzCtUFSElHSObYay065vbccYf+v8uGotZx0oUknAiw9HR8uvbTNJZjQ33/55NT/zV0725XJyiYordfb2UtVJNe+LACPfvLtxLW46M0TueIJbKks1p7OgJFyawAHb8Afqd8aOsJyu+3/Mj0FoRl2uxtXuczYe97v0CSgpWzCxSwl/+EQ4+CH/3A55rvoA3/fhJekN6frP3XXBirWs46/nMZady9SWn8C/7z+ShlR+H7b+DR66tdbUUirnAn4EXAmdZ/m0Gbjf+7kRXxF5tHiCEaAJeBmyo6EylIjT6jrymMRx1zLTmEwNpsO8e6N1cfOr8GiaJVaHLaZJ0TuPIiEfI80rC7HshC1aEgFVB690CR+xdODaR5o6tvdXLX+RYzxNNZicdetuzzUm7YDU2kebQY79FHn6seN+JEukBOu8rTrMgHZ9lMK0hLYm+SWkdA2H7midrEX/bPVhRwu7GpN5WETpcmJwIBKuyrk+gMTqRtiholiAhIu8QWnScuYYq6lAWJhMd8/BIjE1d7hGUzTaaExOxVJZEJocmZZE1qRTNiX6akoN64DQPSipYJaw2zl3u3t7Pk2XSVzzXHeK5bl3ZjqWMoEMlmEhlaUiP05wYIJ7J5k84OSOV3gZhe5bpeRGfPRoiZ5kQKTy1Sp/I2nemW6Qm4fDoBIdGYgU3UnO/kU7vwixWSmupeh0jlLqJy/WjiVLQFDPLg1+DbbfBpV/k7vrX8M4bnqK5IcCfPnkRL3/+kvLHK/Jr0q66aC0fOvRyti+5Ah77Fuz+S62rplDMaqSU41LKndZ/wAQwZnyXwA+ALwghrhRCrAduBGLAbys6mZdVO5OEnqd9FbH5cIgNB0dIWnNL9T2nWyhMIdhl4XpeQQMjYIXXGZyCXGVBQmKpLJ0DEf18+UOkJcpe6eNNxWwo4q6gVSzYdT/tohTJ8ukF8ntWfu5Nh0YZi6fJRoaKN9ZNITCGHywWqsbU1Nb7gb39adOaoOV8uXYWdAPh8qO3YiGlZN+eHSRTpZT0guKR0yShuD729fElQIKQLu57HhbYyaqMXha0pnAXwmVC5tBwjIc2+4j+aUSjXDTmHb49kEsWR2ssmlBxtCybyj+HpNUSNTFKfazb98SIlJLH94+wbzBq/VFXJC2BUPz0q28LnuNamrfwEcOiZw1gYr3usVSWw14TUG7FW7wRC4ZI9zoeGolxaMRU4nKMxFI8c2SsqOH7BiJEk6YHhddDsHw/KAVNMXNsugGe+B6c/QF+Hfx7/uG3z/LCVe38+ZMv5dRl1U8xdCwjhB7d8V3nn8jbu9/KQOt6+L+rYXB3raumUMx1vgV8H/gJunVtBfAaKaW/cIGpmOF6aAhspiQQ7tHXBo3u9x3QIu+e51QwRg9CzhCuXJQAzSlweOLYwZkoWUp29oY9w20fGZ0gksoStwqusrB+y29eKNtuWk7PAUX5GXFXMnGj7vrXnlCCu7ZX5lpZybm9cnGlsxrRTEC/1ocereicwve5CyJcMDtRRvgtX6br8YefsAWg8aItvNcoQ+AVbMaNkcEeogc3cnDbk577mFYUhG5BsVmVLWPWOdzMiQqn4laFZUeMxFL62rZIP/NGd7gGfBhPZKjLxbljay+hCbvLcyqbs0+8ZEtHcFzR/yDsu8d9DZpXg/bcmZ8MyhvepYRDD7NobKv7MS4h+10nOBJjuiumJRCK+/iz30lFe8SG7MHORg868r9+tpz0AAAgAElEQVSZk02m27TRDpexJSU8sX+YbT3jtrrsHyx+dBfuW8skgpuia7GUjU2kGTOvo5bj2SMhRmOpgmukZSza+kJKPU2HMdFhRtcth1LQFDPDrj/DvZ9HnvZ6vl3/Mb561x5ec8Yybv3IS+iYr4KBTAYhBN9483recPZJvGn4auKiGW5/94wvDlco5jJSykullJ+yfJdSymuklCuklE1SyksMS5s/Ou/TXQ/NxLamEH30Kd36FWwuOiSWytITiiOlJJ7OkkjnkBbXICEcL3MpC3mZAkG3Nlm/uYkyhXJs2AW+SELPn7b5sJ9nSkG4MY2HAQ8TWjqrccfWXvf1Ld2b9CiIuWzpKI6e1Sgt+OwbiPJoZ/kUJf3hZLF7qQuBfF9afgw2sb13nKe6Y/p1n6g0JUrlVgYpyqt1O3vG+euGzZ6pCVyP91l3YV3PaA02k+8e99qJnK78y6xhpUvHYWS/R80EEUuqiOFYiqcPh0hksvlgEm5HBYTuLpwyFCJpHf8Wwbk0hfon0jmePDCir23TskggULSe0zi3MVFjixiZy/Dos7t52uoyOZl1n44bI6dJQym19LVjMqjsyOoqdtXNWhQ0KSVZTbMFQRoIJw1XZfd1tyUnDroegwMPFL73PWekJnG3oOUjd9oC2xY8BtI5i6XQYL8lAuaBIX3sm2vkNOkSG8l68K7/g9hwcRuObmRRWLeOZnOF8QlmYBPL/okQDO/Tn23GXs5HuhtKQVNMP4efhD99DLn6XL5c98/85NEjvOv8Nfzsveccd8mnq00gIPjWW8/khevW8b7Yp9DGe+CPH1VBQxSKWpO3oDlesy6BEx7cM8iWIyF290d4YPcg9+8eYFefZR1DkYAj81Ymgk2eVcjmNPb0h90jEprlWDHrOrLPJsR7H+9WpLSvEXIhkdYF5QnDMmcr3nRRNATfyrHPuDvZOxBhPF5ekNzZG2bDwdJrdKDgxmlb15S/xv5a0DkYZfORYqtBOTTL7L5wuUaJdM6WW23gyF46xp4lu/deyBVbRSezNovYsB5QIV8R6zWXrn/ayBsdjD+OPKkHELNYcgoWNPu9pCvQgmgyB1iChAzs1HNomRY0BPfuHOC+nbo7sFlcY2pEF5z7txFJZnysh9QPNN0/o8ksyUyOVEYjmHV3q2tO9NOUcLi/dm9i0dBG6jTLuXwqaK6XKDkOqRg7uscKud08IrEWKRppR72zxcqqeb8CxTn3gEOb/sKSoSfpC7sous56mF/TcQ7s3qoHf/GRY046nik5KfPjwd1uV8A6rvXnaiGirb6tjBNsJl5sRUyGaZ3oBnQFVmgZmy3ONrtkjltjUk1vgrKgKWrN4G647V1oC9bwGfFv/ObZET592al88y3rfSVMVJQnWBfgx+9+MXVrLuCr2ffps1GPf7fW1VIojm9MBcqpoLm9mKWkZeIow5ZEtf3hpLcxSMqCAtUwz7MKnYMxDg7HGPGwBGWzWQ4MRQtCm6lYSAkHH65sSZolkpxIhlnR9wCBnIewW+rRn6+DNrkQ2PmgAt67tI/v0gXzEggtQzATY3vveH7NkxsBHFYZaxlGJcbjaXb2hj0VoD39utBozsS7KVuArrRYrV82oVHays9pGvfvHtAFYIMmUvnz3L+rr7CexizBR3dLKbljay+Hho1jiyIOWlwcfRRY5AyZj37q4hjnpvALezAJQHe7G9qd7x4924TVCqR/BnKFdULmPdI/rt+Dj3UOs8ERRMPN4PxY5xAZTaM+EyGYKQ5I05Aep2P0GUTaEtXReDaIcvkNy/DM4ZCe3DrcA5335ZUO4bSi4W7FakoMwr57IdxbtM3KY/sLVtSxePH1aUiP05Ae99CUNNh7F83xPuMoY6dDDzN+6Gk9+AvAUd26NJHKEk6ki661WX1TbtSkpD+aLoxDo415a5qlvU7dynpdpXQZVs6+6nmGbKowYbDNUFDNuuQ0SUOmcH2FlHZ9O2/1KwRO8VLorSgFTTF9hHvg1reiBZv4pPgSdx5I8fU3r+dfXv38KubiUAA01dfxiw+cy6ZFb+ZOeTHy4W/oApZCoagN5rqKOocLt4ug1Bo9yMLQDjKjXfnfbFHKhpxrSy0CWAnBLqdJhLTLTc3xXupyuhC6byDKrr4IfWY0P6syaUsTYCkhNlRQPm2bC/WpGz9IQEvTEC8dBTCYibGq524CKcuMvFmHTKIoOpo/3PvDGvZ7fuyw7tpWgiXDT7Fs8FH6w0kODntHgmzIRF3Oaq9vdyhBMptzjehnFTC7RssIbfvu0RNzG2jSbkFzc+sKTZiud5L6oO4Om9UkKZeAF5lceSuOGZxh70BUF+zD3d47S32lUKBEygmP1HvOgsy9S+5jLSKVzeUtoMX2EcMaY6ZCtKzjNLeF4mnvXFXGiTKO62neV260dT9scaV0WaPn18UxHc8noo6lsnSHLJZG2xqqgrUvm9Nc+7c+EyGT09iw6wAP7hl0T4ZdASJrd1kejCTJZdOQSbIw5AhZb3ErPTgc08eRlOwZiBhj1z4wrAYpLdCApsHBWCM7esOFIB/mjjLnCPhjb7z1utrWoEn0lBkDxeH1NUt6jUz+2exYx2ZZg6ZZk6tLS8AdoHVsJx2jxdF3nSgFTTE9JEK6cpaK8o+BL/FgfyM/effZKoz+NNLeXM/NH34JP2z+Bw6xitwfPlxx3iGFQlElpHPhuDcBQ+AKWCLBZXL6a78+PV7sdiSlRaDzlmylVZEDhJa1BQfIu/k4oopIKclpWl4QtMk3XY/pa8Qs2GeoZd7ZbCgSd3UnNAWmxpQuQAfDh9ndF+Gep3eRnDCSEh962FNoPzI6QedghGePhvT1MPbCjVrYeXCvS5TFEtRn/CWbXjiopw5w9yrXa2HOtFvX8miGK+iOXrd8Wf6sKdJhQbN+i6WyICUBixtdfiLfo2NLRrs0XQ4zcRqTI/oVtgWIMGshbIJqc/gQK/ofoC5TrHx2j8XzSoEUulvppi5TEC7cN54WRWM/2zg39rW65TkVrbwFzVw3VtdQCBpR4lQSIDqAGD+snyOT8x3QBURRbsSGtGViwktBiw3TGjmQ/1q//16W9z9Sqob62YyGbO8ZZ8NBvU+LEpqj5zpLZjRiqSy7+sJF7W8L7yOYKV6zmEznbJNIAG0j2/J/hyYydIfidA5EjPro1yOZKX4uhuJpwok0W48WpzHIJ1GQkgf3DDIcTaEFGmzbrCO/Y3QLq3rvc9wb3kjpUOD7t0HocNF+Rc8ZSkwuSEkup+kBRXTzrf678XxvjhaX74ZS0BTVJ5OE296NHD3IF4Kf52+hpfzyA+dx+QtX1LpmxzxL25r4xUcu4fN1nyOVmCB9+wcKwQQUCsXMYVo3fMyMm65O1gSzmmERmTfRw/aecT1iXKHwwkvfRZgolFFUKft5PVaqd4fiPNc9nk/dYd3L6hZnCltSahYJXSKpM9qVY8Bw24ylsmw+MkY0mcnXSwvolov+0TD7h6K0h/fkcwRpUhLu2uJav63d40SSWTQpCwKfs6VFa19cvsfH9CAeZdzLglZ3fOnsQ33b3oFIPgjFIUeY76AhaVmv4a4+XcEUWsYeYANduF7Vc3c+MqIX9jVoORe9TssrYz2hBFmLTh/MxorWRmU9hNr+cIL4Dn0siAP3s3hkEwLNfe2QsLg4allaxnTrr3S5D549GiI0kTK2k7dUalLCcHFUxLF4pqiOeduatFuJSl3RfHRH8x4N1Lnb5iwF5i2Uh5+grs86Ll1cMctRiQdR16O0RezuuAGZoSneT3PCy0Jtn5gJTaQIjh9iyfAGGhP2xOfdY96JqIWWoTV6gCVDG4u2PbZ/mH2OHINuVqt0trCWtD49zq7H/2yMG3sf7B+KcXTUrgja3FIxJh0gb5ktQqLnkQMk5rOp9DVJWZ4fEuvEl6Noh3V5W0/B9bkwOaHf6ALJ/sEoh0ZiupI2GVdtlIKmqDZaDv70ETi6ga/Wf4Z7Ys/npg+dzyUqx9mMcdLieXz1Q2/hK/LjNPQ9TfLe/6h1lRSK4w+LwmIllrKEai7snP/LKqxLJPMmjgA4Qtl7CxL2KtgFtSIB0qMMMxpbpxGe2mpxMeseTWbzM9eaU7APmAqaZjkulS87l8vpi+qF7nJnWjKElqPPWAPUG0owdGg7reFOUplMcdjqKSJBj6oW7oG0t2tXfSaaT2rrhlV3e2jPECOxFENRvQ1Oy4/1q6nMrey7nzqHZcUcA63RQwTTEc/2SscaJqdlzDx/PJ1lW3eIhKlQI1kyvJGO0Wds+7tZ0DQp6R1P6DmwdvwBaQQXWTC2HVLFVkZrCeGDTxNLebs3ejSKgXCSSG9n0dqobT3jxUE8nLnALP5ujclh5kcP0ja+h1U9d+e3HTWUkvz4FIXAPaVG1pSTbpc0z/kMEmJ8dow9SzDrPm71eRdLsB4tg0jq1yqQKShkTcnhogBApb7ZzoEsSr/hrjQV2rV06Eka0iHdw6poba79fslJfey1THSD1Gw56HSbaeHZVrjkFoUuVz7wCMCOQ0ftqTk8XHY1x/Up7Q4siaf1ca+lYhAzlGJzvaSvmikFTVFNpIR7/hX23MkP6j7In1Lnc8tHXsIFJ3fUumbHHetXtfOW93+aW3KvpWnzz0ht/1Otq6RQHF+YL3THi33TwVEOjcSIW9ZEmYJia/QgK/vuz6/ZyXkKAQUL2kAkUZhZBlv46/y6DeN7nSPXUrHrmJciAK2RA7SPF9bCpXPWmWf9/3AiDTJHcHSfrV1QUOLqhKBucLveTlMxs6ylMtd3mMJfW3Q/8ya6HcqDRRBztsHDxdGJJmVxBDv0hMCregp5v9oinfbSpLfgl85pPHlghKI1RvaP4nNqdqWjTisEYlg29DjJXvcsD5rlGjSlCoEPCoFBTPcwc4u3aNiYHEaLDkBi3LbGMN/vZhnGZ1O837MsUxDdP1hQ4GJm8AcPrH3TF07QORSFo8WWGystEz35dV/5sTy0m3RWtxwuHnma9vBeWmNmIBO9v0y3yvy4E4KAixuf5/3gYx/fZXlM5EwVIXWF1mQsbo4xkT9nQ7rg8tga2V90TUuHgi/eaL0Xsxa36aI9PXO+Fcbzo53D7OyNUKelmDdxND9ZlD+3NJKzy5y7a67USGc1sv27WDTqbokHWDb4GC1df/Xcnse57tZWG/NBWwhYY1rLU9kc8V7HmjafGppS0BTV45FrYfP/cFPgzdzMG7jtYxdw9pqFta7VcctFpyxm6du/zXPa89D+7x/IDDlzyygUimnDRUHTlTL9Zb57oNj6YAqbpsDulVvJakHrCSXYa5aVGIc9dzI/qgukmpQ2wS/gUC7yoauTpfOcaVLSFtnH/FhXoa4W05GMDTI8Osr+oRhDgwW3K6viZcpQdXWCwNhBo73m2jo3y42tpgWBLxFCyKxlixP7rHpDarTQH5l0Xvm163uFL/UukfisanKyeyu5oc7891JClJm8uOBZ6C7xOoNLOF0eDxw57HqcZlkX05AOoRlrB83IeEJqFuuftLnQ2s+XZfHI0zQcfRIO/M22xtAUfp3pBDzXXpVQNPY7glAEMxN0jD1r1K6Y4Vjp5M2tEes7zbCoDO9le++4a8AVZ660/PfQEZoP/42mxBBSStdgLiCnpEONx63X1HLv5P8ob0HLaRrjJZRck4b0GPNihy2Ki2Q4agYCEmw5Wny/t0U69RQMbospJxHULZHxdvGeSKYIJYrTPDivT8YrXZDlQjTHB/LttBnZNY17d/az87mNJVxBoT4g7EFGPKgbdZef7MF5LEFCjLr3h5PsNkL7a9k03Xu3+NbplYKmqA6bfg6PXs+fxSv5SeC9/O5jF/CCle21rtVxz2vPPJGjl/2UpBZg6FfvQEuVD+2qUCimzkgsSTxTUMhAz91jFUIKM87ON7b+orcpaA6FxVWgM6xn+ZDWjmKtio1ZTnO8l6Yjj8B4iWh8ZegameCI4TaWyubyisj8WBfk0kgp8+G564QohD+Xmu0ToNnIjWl112sP72Xflof1CGsHHmTRmGVG2kPY2TsQQWhplgw/lVeUttx/Myv6H3A5rozEZNm8sy/Mjp2FQCuVBpiMJIuV7kVjz9m+FyvmhZOMTaTRDPctzSHA9owZawcN6nIJGoPFYp5zXKzs0y0IbsFD8gqZGUSD0gqaFHX47ZSGdCEyXuNEPw2pkC032JF8InP3c9nrYArpJdzynC6gZj8nxxEI6jMREpkc+wZMa00JW5mUNKRGi8qcb7qlOtAtzvq+VjfN3nHvSQonR8bi9IdLK60AC0PbaYvaFYpCPYuvjbUf9/dbc5yVduMr+sWtCS7PqacODLF/yE2BtljGbUnY7bkjBYWpDoFkV1+xdUsazzqvHI5CS4PUmN9Unx/jUkoiyYzx3PaLLBpzRYmqDQYjSQYPbCGS8le+UtAUU2fHH+Dez/Mw5/Ht4Cf43dUXceqy1lrXSmHwpktewhNnXsuK5CG23fARpEpirVBMK+msxv6BsD5zalXILP/n/8pli2aOCyGmPdzpYkMQdXMxM4VnvbyJdNYmfJkWrZyUdA5EEEiCZnS9VNS3m5XpQuaGENhkk76DO20umIFAQYgWLoFU3ER7IXNkRg7l14o1pArR3pxWqUwuxx1be8lpknqH25q1n21uoVLCnrtYOviYa5vMM5htjmettfQOIGJiKqR94SSdg9F8IBQvmlLDtu+ZrG7ViSQyHBqJsbtPt4DkHEE6nILf0qEnHe5fppJVIGCx3rl5ihUsaLprXF4wFoL9Q1E9DxdWN68AveMJj+iUTuwiaMfIMx77lWfB+C529UWIp71dUDtGnoadfwSgLbyX5uQgo8baSLNnQmNj9PQecTna7la7aHQLS4af0nOJWWgP72HZ0BOu5zdTFPSMF6Kymv3n597zCohTnkLZbeO7Su6ZyNhTNxh/VXwe22/On7VckVuvscHytzWKp/2aCi1rue8lKcPi2TBRsJQdGrLf+3WOSLgr+x5g0dhzRu404+yapHMwmrd42VvhfX3SueInu1vkUTPPoV+UgqaYGgf+hvzTx9nMOr7a8C/89uqXctJi78Spitrwd1e+j8dXfpAXj97Dw7d/r9bVUSiOWbI5je294wXFSGr5GOxSSupy1jViEg49TLEEI1k8/BTNyUH8suVIiE2HdMHeLhxYFDSLQB9JZYkmPHKd2apS/HtOuudVAl15K9rUt8321aGiIpAILUtdLkk8k7MrTxY6N95l7O8tqHb5zOVkjUZ5YDhG99AY9Zkoi0c2Fe1rttVcu9SQDnkk9zWDcLgXYAYGqVRQS8dD3LdrIG8N6BoyXKZ8CPX5fWSxwgp2l86eUILOQbtwah6fzObYcjRENqt/T2c1wgk9lLqtHlKjazSeb2spnC6XmjNnYAWYbdvj4jps0pAJ569Fa1R3s+1yRNxcNvgIS4afojXcWeQaV0iCTP7edCrTxp6u539gdz/be8ZdFC37rIanFXCSPpbWxNVOZac07s+RQpmOvX1a0OyuqdYyC/uaVm8wLMpG4csGHtHvf+Nc1ufpgpFCbrHxQ8/SZLl+ywceyqcNqTeShjcnBtBkod7SxaU8ndPc3T4LDSxYxW1J06fgD2ugFDTF5OnZTO7297JPruJLTV/ilqsv5cQOpZzNRoQQvOzD32bfvHN56b7ruO8BH4tiFQpFZWTi+Rn8YNYQ/LQc7CoE6TGjMoLxCk+GiySb+bHDNKZGjQAV/pBIxg1rgFMoChnrX/KJeQ1iyUxeqNA0jUg0SveYXeAOZqIsHXy8+Hwe6TtGokkGI46gF6FCHieRDBfc5AxhUUiNJcMb8u5tewcirnP248kcB4dj5OqaXM8NetAUk3kTPfm/W8Od5ALuCkDnQJjBaHnXMZt7Ylgv2xrFsT28DyexVNYegXMS1OWSNqHdXLun+VD0TKWuNdZVGHuWw6yRACWSSDLLweEYC0I7QcoiZdIMDmO1KDxrW9Mk8WtxkRYRNJHJ5dMuWAlmJvLKVLly3capH/LpDyx93Bbdb8sZKPLKmcTLmlJsCXdul3SNTFRBdLeTzmll3PJkRcqdFHVoIlgm/5zrWYp/04r7y/kcMvHqv7ZIJ4tHngYKz9XhaMrYVrjnrM+tpuQgHY7gIEHDirbYZqktRLvMZQt9uPnIGIlMlu094+zoKWENtrplGuO5LbLPtS2VXneloCkmx9Besre8ld5MG//WfA2/+vhlnLCopda1UpQgEAxy8sdvYyLYzronPsXfni0WJhQKxeRJZ7V8OHkTa3hoj4CDejQyC1YlrhTOmfbm5BCZnEYwF8+7RwqLQFksNBSO7973LJ27txQpKm2RzqKkzXraM29xw2o9CWYnbJJJQ9eD+e9WAdBp3QkEioXxdOMiQvF0Qfl1oT5WsGy1xAsKWlt0v219k5Vygqi7QF78mxlExVrzvW4WncpjLtgOWzr0JACNZo6xMqJcTtNs19Bq43QLRBOKp5k3cYSOkWdcg22UwrcLfSaZDxBSisUjm0pYfezXwG9ycecasZyUIEpbZk229YyXsICWHkfz84qm26FOu7L/0rf3jLu65ZnUZ2IEjDVZfpSEZONiwwPA6brnpzZ2crmsr3VzOt7932iJUgr2tCPLBh4FylumzWA8mXp9CU4mOB8pC4rdSNg+1s2UIjnpHSDGpmwaqQPqM5H8OuCpoBQ0ReWMHCB94xsJJeELLV/lZ1e/ntULlXI2F6hvW0rLe25hlRiFP3+SDQfc3DMUCsVkSGdzjDhynO20LGAvUtCMz0BR8I7SjMZSZDWtyD2rJd6TD63dZrgRWYVbodnPY1XYJrzW7rhEcOsJxV3XK+nYN7TEe4uXoOQVtMosS00uLp/hRMYW8r8+E2HRyOYK3cEqX9szEkuxszeMU9sK5FKe+alMSrtMuSO04uh9+WtQRuHTNIfyYvNc8+4nd/e9cpTPFialZHxsqMxeOkVrlaRkXuywq+ucX5YNPU42ON+wxAr6w0l9fVjJMaNvy2rSVWmd3xgsO+byLss+oiKmc97rPCulY/QZmpJ6f7uGpHcgA/VgUdAQwpc1zW2P0ESyOHedB+UskF79G8zGWDT6bPmRZ5SfbligfzYu0luZfx7Zn4/WrvIqeWFoh0ed7GMklc1VfN8rBU1RGSMHSP/q9UQnEnyh5Wv84BNvYUV7c61rpaiAppMvIvPKa3hVYDMbb7nGEDIUCsVUCbgI0VaSjnU50UTG11od0F3AthwJMRJL0TU6QU8okY+M6EZB2LFYS1yiOAIMRJK4GKw8iaSynsKQW3Q/T32ghEDmQ44EYCiaYnvPuO235uQgLXF/USlD8XR5wRCKXMj29Ic5OBwrCnu+oEwQBrBGJ/TPyr4HbHL9jsOF8OLl6u+MZBdOFGb9PcPle1DKcupnO+jjbdOhkbL7QXHbWuI9LBjfRWvkgMcR/hAyS6qxA4lgJJaiJxSvuC+saBIWWNZNVUJOSg5Yglqksxrbe8Y5OGxX9BNTdJX1i+lq6ue+GLNMSGlykqZhg/ITNt7XpzlRIi+fQZ2W1oMiWZ6NmvSeMKpUP7auqQw6Umfs6A3b+soPSkFT+Gdkv66cxZN8Yf43uO4T72BZm/daAMXspfll/0ji1DfyT+K3/OxXNxTNxCsUiuoxHE2y+ciYJaS2TtfohM9od7oiIpH5qG/pMoqdJoKAw4LmFIAkgJiU4Dfo5bZUIlQ7wFAkSXcobtTHWwD0I+hbSTgUKGvwgFLko+iVociFzJKLDgr97UdQrAapnX/xfd2cVhObYl+hJaqc4hwY2182uE0inWOyQRRMl8xKrc5O6nIppAgUuTWm6yeXHkgPAJQov6MLveOJ/D0BBau7VZGeSaQIGJenMAGwYNyeLN10F7QG23G7Z817PN6y2vN8mjAVwskraH5YML6TZYOP5BPB6znMJFo+3Yf9/Nbnlr/HUUGlco9SWRlKQVP4Y2Q/qV9dTiSe4out3+Taq9/BUqWczV2EoPltPyXbcRrXad/j32/4Iz2hymd1FQpFeQYiU39Zm5Y2UygPiNKvbxnQcwfZFTS7MFqfidgW2bvjPiue0ST1geI6uK3jsQpu1lDwArNu7hHhFjQ3lKlbgV0OBcozybeDnCYrdrU0sfanH2tDrSjlKlep1WjCZw6ncrj1V0O6dML06iKL82tJDRkIeh4RdElibtLgkm/OjdbIAYJZ+7t2PJ6edITGauOmSAW04nWfraXW01kwr3Omvs1zn1jrSbZ9y5U1VaxtSWRyRJJZ6tPjRQq21TUz5+PccrKLSz1QCpqiPMOdpH75eqLxFP/e9k2uvfrvWdI6+XC4illCYyuN7/s9TU0tXJf+Bh/9+QN0jyklTaGYGsUv6Wyu+sJ7ufUpWkBXbhZakjpbg2YANFkW3qcmkWOpvm6KLk1aIZCJk4ymeQi9/s5ZnJTbnaw1znYFNCcH8+t6gJKCfbXY7zOFQCU0JStbZ1bKrRYoa+QYjCSJprKTVEgK66KcQSMmg1NBg0IIdjfcUjAArF/ZTp1PH2E9wp/D1blvH61GgBkn0/HsKIUUAUDoqS+qohDp10sLFPd14Zz6vVMq+I+1rKlSmLwplLd06EnP9WSQz5RSGh9rCwHfY0UpaIrSDHfqlrNEmi8vuJbrr/57OuYr5eyYYcEa6t/9W04IjPHV5PW85+dPKCVNoZgCpqsbQLT1eUDxGqCq4LPMUpHprIEjMpMIXOEWadENL8UiIL0taDlN0txQLKLE5q/1dU4/QQ2SmRyZnEZ7eK+vMkc7zrV9XzT2XP5vN2G/EuItq/J/m+OmWpRS5ssFNClHomlZRft3h+JkcpqviIlumHnb6jPRvJvdZHFes8bUaEnXyemykjamxvBSPvYNFueum16s93QVnltmegKP+2Ni3on5tVvlrHKiSo/RvIJmuS+WlJFr/QRs8WuJD/hU5JSCpvDGsJxFEmm+svA6rv/437Nwnn+XEzgsT7wAACAASURBVMUcYc1LCLzxR5zPLv419WPe+fONHJ3EInaFQmG3pJTK1zVVfImK1RAoS5QRd0R+NNeS+CUv0Hicw02QibR5Ky/2NTDlBSpzrU8w5+95l2z2VkZygcm/G9MNCwgtOiv/PdJ+mu9j/czGT6f3nFPwHvUZCGEyyk5zYrDICjwVpMNNuKSyKiWTzo8wSZrr62YsMIiJFMJw1ZMV50Fzw7zHvRS08YXrfZc1b+LolOsDhfVhQYtLY7CMN0BWlL+/nelSvMj4tIoqBU3hzvA+XTlLZrhm0fVc+/G3095S2ctXMYc4613wii/xRh7lw6mbeOcNGzlSYf4bhUIBmkVBkz5nSid1nrKyk7RZeCZLqYAPzlllWcKNyY18ompD3ZzfaHcTFC4CcSlL1YA14EcFwmVjcGrWr7GFZ+VzIE2OyY+TkxfPK1GqXu60Lm9yjHG/QVe8FOjmeu9rMXlrn3v/TtXqmS9dQIcxeV2q/pWS9RvKtKpU14LWGjsEQDY43+c5vSm/XrYyrGsey1m1+sN+A8AIEs0rplCrAkpBUxQztJfkLy8nnMzytY5vce3H30Z7s1LOjnle/jk490N8iDt4c/ovvPOGp1R0R4WiQqSwKhnT94otF+VQSElzYmDazu+Gve3lMdeJec3Uu4tMgoyHsBeZZPj4Rp8BHjwRYkrK+FSObW6w93mHxcvFLNaZfLy6TK7uXha06ZjS0CyKmFWBdFrQSiFKZNkSCNqbGzj3xEU0VVFB82tpqTrGwPEbaCd/mEcPaYHGfOh+N6ZzIssvZd0Ofc5yZILzyNW5u0subLFb4U5dWkppVQqawsnQXpK/upxIMss3lujKWVuTUs6OC4SAy78D667gc/ImXpF+lLf9bAM7elSeNIXCL1ZBZDoFj3LygtUVrPTs9dSwWrm0CgNlCKlx0uJ5eM7Uu3afKLJ8ZIO6FclqcPAb7j4bnEe643Rf+3phBlbwYpFFaVrsutZlcuMkGBA01AVYd2rB7VNYxtxUEh2funQ+z1tSftxMdox7rdcR03HPWMZL2BLkRFKZMlXnFTp9GqqsVTjZ4WR5RVG2LeHkLUrrvAl/uQTdyrGSbFpSZpxMvgOr9Wwr5ylsWvnPXLWgyNJvpS6XRHqoVisWFK5JndCV+pJ1Kl0lxXHF0B5DOcvxzaXf5psffWvJgag4BgnUwZW/RKy9mG/wX7w+8BTvvGEjT+yfesQsheJ4wCpYZeoXTN95ygjfDelC8uZKZ8L9MNpxTtFvlbqMtTUG6ZjnvTi/WGYS+kSSw/JhnndyColAVOiaWUxpBc2ajmCh61IBI0jCJN+32gkXkmpcbCmpPKsXtvCi1YXxWecQoNubG2io9yMi6vu0NgbzirIvHNdq1YJmTlu7hroKpNJcwF/AsvEF6/J/ZzR3ZcTEO1iEt/3MtleVvBIrTX9w8mK7ouI3EAXgqLQl2XLZqIo+ixfFkyrVYmLemqLfko1LKi7Hrb+abK7PZjbr0spcQGY921p35tsLX3xcHqWgKXSG9hhujTmuW/YdvvnRK5mnlLPjk/omeNftiNXn8/Xs9/n7+dv44I1P85dtfbWumUIx67EGCcnWewusy9uaXNdYlWJk8fl54SOd0zxnagHWdljPPXWpcXzBCwCXdWKWJlTq4vj85d65kZxlQyHPUEdri/13n8Jftq6l6DcJBFzyuVVCIbCCO9Yonm6CoFn/yb5zRV09mfpW/W+fgrnALiO6BRvxU5JpGdE//I9nZxTH9pZ6WlvboGWx7zJK5day7nPiSQULqS1pt8u48QqEJqTG6oXF48dvVFEnmiOoTHFOwcruWZ8BVV1psATIsI5joVWa866UElvqHpu8dc3NMpcLNlccCdXtvrH+ZHXJLav8erjOVvq8VwqaAgZ368pZSuPby7/DNz5yJS0NSjk7rmmcD+/5X8Sqs/l/yW/zkSV7+fRtz/GThw+UXfuiUBzP+I3c2BAMoFXozpVqWkJ8XiEcu1ZXEPLqHaYHW9FVuGdzdc0ABSFVSoRF5Giur6u6S6fWutquhBrFNzXarVCZet16kCsTVGF46YXFPwpBWwUJsd2QIlAyB1LYsjYuIESRoKa5KAp+gk0Iy6e57sXvFRAODW2Zi0ucP4HSVNAqW4fnugatroHcUv9R/fyQqW9DBKwKSKFdWqCO4SUX2esFjFkialppdlgURzvOI9x+utOG5qteVuvdyYvnFw8fl2Ksky6mxdTEeXx2vr9AFScsbCFo1e4sA6NUygE3gtniQBrPX9pKU32w5P0hEa5J70FXwEolrD9jRbvtu6k8VZo02reCu/jUspMgbhNG8eaVdoXPT518VklxrDK4m+Sv3sB4SvKdFd/jPz9yJc0N02OKVswxmtrgvX9ELH8hn498g2tO2sO3/7qPz/5+G6nszIb+VSjmCqYi4we3sPSmpcpKuP0Moq2nFJVv/bvJEegiUKWFMY3BOtYsKlgOAgFosSgPpnUokcl5WvQqCcZgJbP6fJulxRTql7YXBNXQwjNJNywEdKti/ljDomRFc7jENdQFaEBj5cIKXPNc0ER9kcBsxXoltMXF693col+2NpWfJF1rRHAUAmLzTybV2OF7WYJTxlw0r4F1DoumH33LFIQFgnjLarczeR5ZxIITCVbi41iGJStPZN05lyKAdMNCQgvPZGjVq/LbtUBjsVIZbCRhyUlnIqTmorBa1b3CL/4oHLVoXkOR0O/m4mi3Vhf6aWjpS4uO15qK3avrAwHbvWzi7nYLpVrj9uyqs4StN/P61QdF+bEsdAuq001Tr0GgZBCfxa3F9/RpS1srVi61hWt97xsso805x1Tv6jcQ6nhxxU9kpaAdz1iUs++u/B5f//CbqxqBSHEM0NQO7/8zYvX5fKD/P/mf9Tv403O9vPsXmxiJeSyYViiOY7wieDkRuM9QpxoWFf2WaF5KpF0X7K1KRmz+iXnFbYEjQphdRrCuu6n8Ga+vy5H5ej9vWav7GhkPid50fbSuDWnxZSESnLWmo2htVn3Qus6vFTclwNXd0qV+LctPRUwpRD5odY3EWk8qnMZRH6vwnFt6Bm3N9rq5XRPT5TDRvNz4tFtETl06Px9kQBhr8yZaTqA+GPC1/ijgrOX85dQ7BGHrHp7Xy4z4JyDWenJ+PIIZtc4jQqclSEik7TRyay6G+UvKrr3qW/nafJ+YeKVJWH7a+Sxp1xWS4aUXEZ93ArlAUz4eo36vOvrK8/7Q3HVNR1+Xs+KamIqtt6XUXo4m6m3Xw2ohygbnF60hdBtTgYC7pep5S6wTFP4soVIEWNhSrNSbWD0Jyrvd6i1z1c1FwFeuP5OO+Q20twQ91926rVkD0Jad6at8gWDVwmZWtDexfmW7x73mXl/rvsqCpvBmcBfJX15OKAU/WPU9vv6hNynlTOFOU7tuSTv11bzywLXce85mdvaOc8V/PcHW7vHyxysUxwnC4Te2aF5D0VoIq3DZGPA7324RzCzKRK6uhUj76ZywsKXIRU0I3a1GP7pwHr+BFexlCZuFzpxBLg487iF2GFa2aNupACxtbeSMle3u+9rOq5+ryLoQtLbBff2XLyFTgqxv8VwzYloBTltWsMad6GKBMNcTmULxwnl264LVLVwIwSmO6IjmcdYqp094KaMd5xa+N3j3l/W4AP6DpVj7VQhZbBmwfF15ml4Xp4XOtJo2NOrXxFSM6+sCnLCwxdWy2BisI5DToyk2NLcRbT0Fbd4yo/563dMNC12DPchA0Gapa66v44Wr2l2ttMLo1zUd1msmGe04j8UrT+Z1Z65BIuyCs8OaeZLhVihkYZQVKYTmho5TPBW0dL3j+hnnXLdCV3CcXinWOiUblyADQbsuaLQ31bgIGQiSPeUyRjvOy2/OtrpZM8l7SJmpKoRwc+/zo6DVccLCliKl3sS8J/TJA32f3tVvYGLeCcVllVmDVkpBE02Ffj3rhIWsaG8u6R6cbHIPICIqiEAbDARYtaCFpvo6V+tevGUF4fZiS3mlHuBKQTseGdhJ8pdvIJQW/Gj19/mqUs4U5WhogXf8Bta/lXW7vsfG9X+hnhx//98b+e2mo2pdmkIBNNXXcclpy/Lfz1jRRrrB4WpkuVdO9hHGXMeuoJmz5elG3bWvwRASnm9RJASCXNB0gbQGRqhMSjDvbZG3oNnXnVVUltu5SwhG9pVDFiwKmkRYdhQsnt/IuScuKgqh7h4gREJ9s6uCpol6wu1n6KUa9W5tCrq/K43tA8tfqVcvYE9We8LCFs5avYD/z955x8lRXIn/W5PD5py0WoVdSaucEEIIiQwSwQSDwdiAMQ5w9h3OgAO/O8ezDxuDjY0Bk2zAYLLBGIMxOUgkARIgEBIo59XmMPX7o3tmevLs7uzOjPS++oxmtkP1q+7q7nr1Xr03rtxPsdeJTamIcxdU0CJCoxfU0O0Nt6W0Z5cp0kqNE+tSFxv8IMI1U8cuA6gq8tBaU0Rh1DErClyhdhlNideJPdCLdhcz0HwsKCNdgFG+cSCt7HT6w0rGhIoCpoWUehWsRGj9pvrjY+toWovcDnvIwhzQ0O2toqduAS6HjSWTqpleH+7kR1tTw+fJkKu1tojJNcZ9FjPvr3JywgTyOkEesHSsnYoBotWY4F+NE4w5e57CMgbMOal9zkJwRA7YGBY44xlVU+QhYJ0ru+uDiJId/Z0pZdLKBgVVKEf8ObfWAC7WOtriBR5JNj9NqaQuhcpfYUQArS7E0TDHuicQq0wnCmSkbLaY+cPxUhVESxJPMm1z0W6xJIe2HeSzVxS0A40tb9J9w3J29SquHvMrrjj/xITuAYIQgcMFp14Pi79O2Zrbebz61xzZ5OSye1fxrbvfoKtX5qUJBzYK8HrCyoMx8mu8lMeW+yh0O9hrCfld4HYkyItFRDJmq2KjVeyIcvCvIo8Tp7nO5bBhd8SbXG+sTzbxPh7RLktzGktotiiErbVFqJTh/FXUN2BPrEwYHRodE+NEeaPdQFVIxqCFK9qisq8obMkMJnPWGkPZi+o47Syfz+b6Y0JBWKxrBxoOjtjWOg8wmANPKcWektbQ8lK/C4fdRrnlWhd5rfnyjE6j3eJ+Fuuylri7FtxUoVEKJtaVJ9w2ep9k2KOCaxj7xXZRfe5wEIignGE13tjTGoLfZgPbQA/a7mJGQwlLWipDlh2bOedQK1tkTq4I5Ti9AUGbxRoWHGgIWheD1Shw2yMD7ERZ0ILbuXr3oJTC53LgtNvoG7uEPnPwJXROnF4qSw3FpKrQHTFPKxgIJhy6PfI8xp+/Z8qunDGBfoLRYscUOzlpZh1uhz2U8D2ee+P2qoXsrFsCNdNpKPVRXeyNI4WxJPV9bBw/0LQYqmPnzPY6iyMHYyzXsctTTVmUO3aEtS36ONiwpXBxrC32GgMEweNoHTpfTrtirGlB7fQ10OuKdcnscxahCA+wBPvE5eZgj5Xo5m+bsjxm3nC8OXfBe2ln3eFsrV7C1rqjYMIRSeslCtqBxJZVdF2/jF29Nn7T+CuuOE+UM2GQ2Gxw5PfhlN/j3Pgiv+36FlcsUNy18mNO/s0zvLNlX7YlFITs4fKDt5TmBcuZcNCyiMh2hW4nkxoqGYjKFRXPHc2an8rA2iuwxewT1zBlUxw2qdYYvY7Tn60qilQMt1dGKh5BRS/Y+exzl9FeEJ5nVVE7Dpfdhs/loLrQg9Nuw6bjd+yCQTDiKhlpWNBiHCkLq2itKzIshpYQ94XecLCF2E5q+CS5HXYCysmA1thcHrC7aa4KK8Td3qqEMlFcH3IdjRXYOIZdKQJ2D5trj044+t9QElbs4p0XuyX0eYUl9HuwE+u1RFq2dmwVClth5ByteNhUauuNzbRslfpclPi9lPpcsUEmEpQRu9ii7GlwDHSibU7sNhUxfzJ4uoxrmo51Kcy2qkUhpajM74pQeIPEWgIjj+HzuiNcUIPyROcEm9ESayEBqCk0OvV2m6K9cBxtRS1Gfcx2XuR1RljsgkS3gQnmvLA+ZxG7S2dEWOB8Lkc43+JAX6jNF7hU3LIAir1Opo4fA25jUCWRW2HA5kgrwIZWNiMlYYKBA5c9fP9Zlfoufz3jKwsi8s0N2L0R97j1ntlVPjtmsMKq4CmlwF+BKUxQupiIm22FzewumxlXeQ3YHMa9YEZYnVRTGOGNYCXaFXJSTRH2ima21CwNLRtT6uPYqcY9qFAsbq7kyMmGNXxMTTX9zgICDi/4YucbWxEF7QBBb36DzuuXs7vPzg0TruaK805M6H4gCCmZ+Sk490FUzz7Oe+tzPLpkA7s6+jjpmme49YX14vIoHJiYFpfiynpKqxqIiV4d576IN4chOmR+tItjf5QfVWRH1DohyWZ2cy1BQsxvj9NORUVVaI5NvyPcIZlWVxxyv7TWocddbtSjsBbsRkeltbaIMWU+FCR0jWoraqHXVUq/w8/u0hn0+S0BL5IkiY7u5Pe4y83lCp/TYbryWTpmVjeyFBannRXz6fQ1YHe4weGm2OuKmRsWs1/oX5wQ8XHkDthdCZUgpRQzGkqYVF1IQDliLFPWTqo1N1d5gYt5Y8tCLoFgvUY6lI9sW9WhKesC0FJTgnPiEuzO+K5qMxpKmDD1IOwVE5nQMh1PVAqeelPRDMsfVOzDMoX/N+tmyl4fJ3pmqK2q5Mm/g1tb3YT7XCWhOU6GC2msBTDVu0nZXUyrLw6dn0SpBlLlrKst9qJ0IGQJD1oQFcYAgcbIa2itS3hfTygATFvhRAJ2Fzsq5tFXNR0wrnco36LF2rV4QplZ18h7alpdMYdOKDes9aH6q4ivIH3OIlQ6Chp2414wnz3dnuq42ykVdjWNXB4+8IDdQ7/NE5LFZbfRWlfEtLpipk8ch66aErFvoGZmuByA8Uth2mkRlWmpMhVc0w08nJ8y/nMhOCCi0bjstrCbsDMqKq8nUrlWyobHaWfA4WdX2Wx2lc0O1W136Ux2l8+mzO8KWYhD1u40LNjSQz8ACGx6g67rl7O7z8HtU67l8nOWx+kACMIgaTwYvvQMjJnPpBe/wzMtd3JYk4/v3fcmF96ykm37urMtoSBEoJS6WCn1hlKqzfw8r5RablmvlFJXKKU2KaW6lFJPKqVifXjSxKZU2OXLdNeLprbYS+PsY2M6gvHyUhkFxT67E4ahtjmoKTbKiZ4vZlfQdNCJlM88nn2FE9HKCJZQ6nPhcdrpLzdG/u2hgCDmqDkKdBx35uI6dpfGj4TW6R/D9qpDQNno9I+huyzs/metT3txS8jiAGbnWOuQ1WNPsWW/CGItB8miVSplzN/bXTbTqJ/Lb56T1NYgh13Fz+FlsqtsFj214Y53hOIVVEarjHq47Da8Lrt5XiOJCFxhzU0VR8bYbaEvTlCRbVWLwvuY17WosoGZkydB/Ryomx3f1a661fCeaJgLpWEr6ryxZWakRghfg0jFpt/hRysbbcWTQvvZbca+DeWxVgpdWEd7QRP+cfMj3OSiHD5DvxLOn1c2wy0/dhdjdaIesqnkBwPgJMtdFVJO4xVj3u/dvlp2lc2OCRak0PRZAodY6xp0g5xeX8zc8YbiM+DwM1DWHNqm22NaeQssipF5XwatW6HyrOfIdCn2+Y1zb/Wi6vCPpdddFjFPbHfpDLbUHRWqa+hQZlu2WZ4P1rqF9b/4QT4ilijFvopw7jmbTeHzl+Bx2o3BH0tldpbPp7ckvvUyLFxYmq6i8fRWTAsnFFeKrdVLImXRmgK3gxKfi7EVUW1yzMERzxJlU1Ay1rJz+Fx3+ero8tVhM8eMOv0NdPkire3pzDkMbZv2lkJe0r/xdbpuWM7uficPzLyOr515bEp/XkFIm8Jq+Mx9sPRSPG/fxXUdX+WaQzp56r3tHPPLp3jg9U1iTRNyiY+BbwNzgHnAE8B9SqmgZvEt4OvAV4D5wDbgMaVUfH+XFNiiojrGs6DZlKKq2Eu530lbUUto8r6tZEwov1ei+UezxpQwr6ksYsDNYbf2KO3UFnuZN7aUhtLIDpZNKUNh8JVx8MIlHDmlljmNpSEr0oDHsFbZnF6onwsQ7lCWR3Y2AXTjISELV2osCo6yU+Z34XbY6SufEor0aKwLFm61qkQTPscKoKAKKppjzlnQpWt36XS66heHlttt5nmYfnpcSSv8rtD5bSj14nLYIkLEB7umx7TWUF3koctXT6AonEcrdDXGHw4tx5kHjZx31+sujem4WV/TdourbMTYavkEqJ0Z8U5P9naPDNwQtYfdCeUTmHfoMcyoj82hZWVKTRGtwfDqTi+UT6SvMdJiF7SaVNQ3s6n++LBCgcUqFed6et1O9pZMxe8bXG66GQ0lTKoppMxvuM71lkVG0YuOOJowMqCpeAQHNJIFdpjTWMqxU2sitzGjUwIhRb7LV2cxnRhfjv6OqIHyWIup22Gnojjy0bOj4iA6y1rpcxWzsX6Z0d6DmNadzjh53EIqVEEVNMyjfsoCWuuKIgLKBOdn7S2eYllWCg5PzPnSym56FdqZXFMU0e72lEzDoqHRWOaPsU6H5wAalq0BVEhEG0DDfNMqZrh02m2KArcjJtBQxJ/Bc28Pz9nTykZ/WXNEW+t3xreUL2mppHLuJ4y5Ya6C0AGC9/uEyoJYi2rKAZPodcZ3Ov0iUdD2Y3o+epXuG5azu9/F4wfdwJdOOXLQUWQEISU2Oyz9Dpz/MArFCa98npfmPEZLmZ2v3v4qF/3pFcmZJuQEWuv7tdaPaK3Xaq3f1VpfDuwDFirj4fhfwE+11n/VWr8JnAsUAmcP5XhBd7PQ/1bLS+QQMmOXnktp00wWtNRC68n0lk1ie+UCtlcutLjnRDK23B8zsj2xqoCGUp/hAmezQ2ENjF0U4zVhfRd4XXb87kiloczvoqrQQ1NDHZQZVpOA3cXA1NOgKGoO1rgl1lqmJOCwyKxsjK8oYHrrVCZUhTvl/Q6/cf5qZ4a61sFgAla0slhtFDDuMKidyUETqphaFxsQoNPfiPaHQ79bvUW10xuTbFsphdNuY/YYIyiK024LRWi0uhl6XfaQW6JNKeY3lYVlAvCXx7pLAbaJRxGwexhXEamQWDvEboeNGjOfV8TUhLIJUNEcsV/yKxBeG+pERilJPpcj+fSH0ib8bocRGASMCtbNAnfwXJuKpLcEpp/O1JaJLJteS11JeO5aSIo47q0VBW4WTaygpbpgUAnOx1X4mVxTREGCCJbR/eGQtdT8ntFQwoyGEnAacjZXF0bMS4yQOyi+TaWIgB0n2bT5PaWmiKWTY+c6ep1249qUjYOSxgiXuhKfE09pHeOnzImQPYS7kI31y+j21QKK1lqLIm09l6VNYLPjc5rXMBSJ0Sivx1PBxoblbKk5gn5nATVFnpi6h6LJKht+lz3i2RaMLhvEYbczrT7aNdD4Dg4u9Fvy04Xmk5kbOex2Zo8ppdhruDQrZQQbiaG/O1SfcDTQ+G1oa/USS3APy3VyBueGhQeFgmWU+lyRz3BzfTzrdyLX2OC91dOf3E0aREHbb9m3bgV9N57AngE3zy++mc8uP1yUM2FkGXsIfPlZOOgLlLxxA3f2X8JvD9rB46u3ccwvn+KhN8SaJuQOSim7UupTQAHwHDAOqAH+EdxGa90FPAUcMpRjOO22SOUhUfQ5ZeT6mt1YSlWhB+xO43mt7IbLUdSzOya8fWF4TpfbYQ+Hh1Y2aDoUimrxWeYODdg9UDszsgzrMaafjk1BY5kPVzqBpFymG5JZRnBUfmv1EmrmnhSzeXmR3+h8Rh23qtDDSTPr2F1/ONuqDjG6OBXNbG1cxpaapaGoilGCh35Zny8+twuv00GPuwKtbPR4wkqZ9V3Ya+ko9U08jk31x0WWHjQwWebR+GpaKJ99Eq218ZP02pQKzVHqdxWDP37uJTA6qCfNrKM1Spks8bk4eHw5h04ox2G3hY7vd1qU9bi5v4jtuJssbgkrBCGr22CTdPvKDGtjsZnPqr83YnWwvbscYRmcdht+V5xBhgRuqBUFbpRS9Jvzt8r9rrjBVuLdTR4zOES0khmjoNkjy3PZbYbCbSpELruNYq8rzSGH+CjLQSebilLw0vjdDktExziKhLsYxhwUcS2ddhtLJ1XFJKWPPGh4e9/MU/BNOx7qZsfMnYrAFYx8Gnk9Bhxe3A4bcxpLY3Yp8XmNNmQ3AvPYAr0x28STKbQoqMiroILmJWDeijFugMHAPzrcvnZVzGNjw/LIfm2wTZY0Yok7GldZ6ncW0OsqYWyZj8nxAoIEFTFli5zPqQfAOl8zwT2YqLsdnIuWDqKg7YdsWfMC+uaT2RPwsObY2/nkUcknCwtCxnD5YdnP4dyHUHYXy974Kq+03Mysog7+48+vcuEtK/h4d+ocK4IwUiilpiul2oEe4HfAKVrrVRjKGcDWqF22WtbFK+8LSqkVSqkV27dvj1hnDbNv6GeJBiiSdwOjrV+TagqN0f5URHUeqgrd7C1pZUvtkTGWl7RmrSc+UMRfTaY1qN9ZQENt7Kmrs1r9QiPSQUVWEXAVom2WiIzYYqJfBlk0sZKGMr+5XaR7Jxg5oTbVH0/AHo4aZ5W2tsTa2UrSs7JwyMQKxlUWxVy2CKOMeal31x0G4yPnvETvmGjwtLrIE1o3vsqw6PjcqRQ0Y/uZDSU0zjkupOSAEXI8SGjPwSpoQYIR6HrbI44bdOtzuCKthSoiYk5QiOSd1YDdTXvBOMbVmW6EpqLb4y6n11lszGurn2O4w5nUFXuYWFlAbXHk8SfXRnbCQwpfdH6yOFbOGLnTxjgXZX4XfQPG7whXQct1dwx0pzzEYA7f2x8wUkh4ig1X2HSktTlZ3Bw5mNDTHzAUsaiDe9ymkmgqd/aBZHPO4yho5qIyv4uGUh8zG0vomHA8fc5CYmOKmJZpmwJsifOimVZb3AURwVAaSr0hV8qKAjdHt1aH1lUWeijzxbG6WtyqF00dz5hS0wIcGIAqy7Rkc3At4TdK8gAAIABJREFUXt2MI0Su88UbqEiAKGj7Ge+99gzeO05jH162n3YPRx1yUOqdBCHTjFtsWNOO+B4FH/2LG9q/zN1TnmLl2k0cfeVT/OGpD+gfSG3iF4QR4B1gFrAAuBa4WSk1baiFaa2v01rP01rPq6yMtZRoi+IRQ7Dj5E4+xc0TFTLaYbNFuNdF2BKqrIE0LMectIx9DUvp8SS25sQnvW6hSvDbit0Wdv0LbRVHaVVR33FDXptun6U+JyVuY8sBS96pYOdfxQloYh2hT5XUOZAo87DdSPzb5bUqoJFuo2C4nCYnvfPrcdhDkf3Cu0Z34cIqalOFn6q6RuqnhQdolVJUVNSE5vQM4vCxlJoueBUtEYtt5jwg5Yucjxi305ogeXOQhlIve0taYdJxRsfbVHS1zcn26kPpdxZC2XgoDQdtUErFtTA1lPpYOCEsU6j+Tg80HxNO95Ag8TJYgm00Lkwqd0gWS9vuHQiwu3Q6Aw2HGHMRrccEZtb6QvInLC+NaxUMGNQfSOP9GhUdUZvzQa1MSWAl1kFF1umF0nHsKp/L1urDwpEpIy64ipAtmrljSyn0OFFOD52+Bhw2W8jV1Lp/VaGbidVFEZE7ExEoaQKg31WIzaZCLpY2pUJKUp+zyGg/jQvi1dA8to0SnysctEkHjIA5QQ+AOFivYfQ1i/F+SIIoaPsRK595lOp7P0knXvrOeYDZM2am3kkQRgqHGw77Blz8Iqr5aOat+x0vF3+br1e/wo8ffosTr3mWVzfszraUwgGG1rrXnIO2Umt9KfAacAmwxdwkenJDtWXd4AlFtYtDyVij4xk3oXSYYm9UR7Z+DoyLtspguBlXWyMkWo7q8jHgTuLmNByiR5CB8RUFLBgX2Uk/fFJV2HoW3MdtdrYs88JsIcuZwZgyHyfPigp8EHTRtLtCUecGVKx1KV7ExUQd3XiLE+ln2J0w5UT2WiJLKovO6XLYOHlWPQ2lvgQFmCTJAxcpXBzpkljQgoyJOn7TwSfRuuAYVHAeoTUi3WCwOwwXPFdk+cEcWsoeWa+4gRNS5IGa01jKsum1SbcZDNb8WRFWGE+RcU85PMZ7y0KgOhyZ1KaU0e6K4wXhiIOl7TltNjr9jTjL6o027ymKuKZ9dfOA5EpYOtNUJpmulGnNJqieajx/okPvWwgFS7Gs21U6i96ipvBGDXPpdZfS7yy0DADFDtkcNaWa46fVmnWJFaeu2ENjyyzqDjkr0o3QEsG0ua48cYAXC4HiMWxsWI42Ledx91DKuO7xBsgSBSYKmAM+DfOh9WTASIuQaPdo0pE9SPq2NiFn0Vrzj4fvYdFLF9FmL8X1uYeobYiNsiUIWaG0Cc64BdY/j+PRS/n8pp/xydqpfGffGZx6bRtnHdTIN4+ZFJHrRxBGERvgBtZhKGJHAy8DKKU8wGLgm0MvPtaCtqdkKpPKAyk7qGC4N85oKGHDLotrcNn4yI0SdbBSzV1LxiDni6qo/ljZ7JPAHdlxieycmL+9pTBpcijUPRBycYqXxDtE2bhQ8BKbz+iUdlutWWay5g5/4pHuRNiUCh17IIkMyuGJqHjwV3TEwBgKa2AzUDk5rKAOhYTuiZbzbFESQkuLG4yP1sN0bY09YjCHli1q0MF6lJBy5I2d2xSxj1IRbplgWCTXbmtPvFNFC/S0x94jhPOvQZxcgyWNca0igfJm4JnwgiQpFgDDDbPDcHUOBqpQKKbUFlLicxpzTK3Uz4HejlAAnHhXw2W30Zumx0m4DQ6CwhrgfQbs7phVweZhVWi7/PUkSlANhlV6oDPWguaIOufbKw9mTMSxFM3xrOVBIXxlEc+JoRC8N+c1lUXMP423ZcSxQ4sHwsvNaKxjynzs6ujlw50dFHoc1BZ5jNg5Jd6Y4D+DQSxoeU5P/wA33Hwjh730JdpcVZRc9BgVopwJucjYhfD5J+DUP1A8sIdr+3/A4xVX8u6Kx1n6iye59YX1DCQcrhaE4aOU+qlSarFSqsmci/YTYCnwJ21EmPgV8G2l1Kmm2+NNQDvw52EcNWZJR0EThS2L42wbS1O5P/1R15jJ9ZGv+IlVBfhdDpqrBp814ODx5Yyr8CeY5B55XJtScRWPiHqYyhUF1TGdLk9o1D6Sxc2VTK+PtQLavGVsqjvGjF5n4vTC9NNjIsoBKVPNuB22kEtU6JnUfHTMdrEhtE3LX6rHmLvAsFzUxHrWNpR6mdeUWnE3BEijC5dMoUhHOSuOkxctSVHatGLaouegWRXZolqYcuKQlMOpdcWx1lQrDrfxrklhlU45WBEnlQSl44zImckYv8TIEQrUFYcVHofdxpiyONbUsvFQMz1u3rUgh7VUxgTqSJwA3fgeVECuqla21BxOWWmce8UssMDjwOu0h6yQiS7diTPqWNKSwo3aTEPRm3ZaDpO4QYLSJEre+lTKUzDSbPQ9lsAFNvhsqy02gqcoM5JrRUGs0psuYkHLY7a1dXP9Db/l63t+xF7/OKq//DD2wtiwrYKQM9hsMOMM4+W84kbGP/NL7nb+gFdd8/n+/Sdz+4uz+H8nT7XMUxGEjFID3GZ+7wXeAI7XWj9qrv9fwAv8BigFXgSO0VrvG+oBdWYMFCGiJ/EnJ3ryuuKo1jjhqZMWYZRR7HUmDUwS7IB3eWtR9fETSkckgg5GA4zD3LGlbN3bQ6EnNvR/9BwZMDpH2uZMe4An0SWxKhG1xR7e3Lg3HA47ThS84PZFpgtqqHOclhTxqSnyQkmSQBVWoqIpqHidcqubXbTVKBWTlsW4/KVib/EkI9BDUaRrovXS2+2OQZebKeY1lbFlb1fqfLB1s4xPZ194WcPc9A4SCsvuhCTBDa2U+lxsddgj0hEE8bsdoaigQRK5fgZdEQfVBpXihHnNiVYB4PAUMrXOxpa2ZMFAEkQHjdbmGg+m3dMKm5NYQuMJkST5fDRBBTxosSz1uSj0OBJGXo1h3GJo3xaTszCeZTaeqJlAFLQ85YUPdvLgn67hiv6r6ChrperCB9JylxGEnMDphYUXw9zz4KXrmPXsVTzo/i7P7p3Lz36/nIaZR3DpsinhibmCkAG01uelWK+BK8xPRvA4kwdCSEW0u1w8BSVx+P5hOMkER4rdaXRoLNH4dpXPQZXHt3Ck7BSbuB12GstTzN2yEHSdSiswAul1orxOO0UeJ43xrB4WFjdXhiLElfldrNvREfo7I5Q2Qdsm8Jrv98Ia2Bc7JbLY66RIx2kbFgUtaX6zeLjSvwYhlJ1O/5iY+VJWi0/y3GEjS32JNyZ3YFKG0uGOmv+YTntz2m1xrcOJSGRVt86DzAShtjwI5Qhgan0J27YEIy7Gcb0e1LMpjtKXAq/LzrFTa0KBSZx2G0dMHsTglNMbEXwmLEqGR9ySIApanjEQ0Fz9+Lt0/vtX/MjxZzprD6LkvLuT57gQhFzF5YdDL0HNuwBe/D2HvHAtiwL/zcq37+CHb5/ElKWf5HOLm7P6QheE4bC4pZK+vjRHbYdNMDKdD/o6U4YxT4q/3AhEYgnekfiw2b0/g1EukyV/LfI4aes2rCFBZSF5xDzF4ZOrYFVytyqrwtxQ6qPM7xpUKO2UFNWFLY1TTjKCirx1T8xmSydVwc59sOnDyP6w3RUxp26kSKV8K6CtaBJ1Pe9nJCfrwvHldPTGRujMCUyX3YC3HPpSbGtl8nLY8AJ07syAEMO/3sdNq8EdzNUWstYmLndsedhlsLbET23Q4h7HNVEnmOKVlEG2m3zvN8gctDxia1s3n/nDc5T8+7tc5vgzfZNPxnfBg6KcCfmPpwiWfBN1yZtw/M+ZWdzJ1bZfcPK/l3HLTy/mb8+9mjjctSDkMG6HIzwKnY41yiTomlOTjhW5cooxuhwMutB0qBF8IFlOp3QoqEyvUxSbuCiCVKHsh0sw5YA7SVLtwyeH3f+Drn7R83QyMTY+LOWstAlcSYKGOFwpz3UMBVW0HnwMLUd8ZuhypYEzhVw2pegPzuvJwJmuKvIMKwDDiOIuhEnHE6iYDKQIdmPF6TVyeQ2DTFrQIu4nX0VEudGPhZNn1TNrjEV26+BQktQFaRFU8AbS9BfNAqHzkpGniIFY0PIArTX3v7aJn9//Ev+tr+FIxwr0wRfjPOaHg39YC0Iu4/LBgi/gmPc5ePcR/E/9ji9svp3+R+9k5b/mUHzQp2lZ8qmhud4IQjaw9mTGL4U3tyfaMoJinzN5MAQrBZUw7dTw354i4zNYgpa3DLO4uYL+ERxgUUqxYFw5hZ70ujSJ8jFlnYZ56W3XfAz0pD8t0lM+lkF1kZ1e6OsazB4R0RbjXYdg8u4RNuRlnLSMNp5iKIyaE+by4+o3zGf9A4OodDDtwhD7duHk7kPH7bDT0x9lnayZATvXho+TShGxWtWHO98wGAY/Rb7IbFLqd6J2Kkr9qQejjm6tTut5KApajrN9Xw+X37uKD1av5C++q6gLbIHj/he14IvZFk0QRg67A6acSMmUEwlsX8u6f1zLmPfuo+bZS+h+7jJ6m5dTNP8sYyJvliabC0J6WOZPpIgsl3Waj4HAYHyy0sNht5HEuJURauLkIkpE0PUpeo7rKE4vGR5DVcDTZdKyQWtS1hDq0REHwTi3fa4i6MBw29yfiBPhE8Jz/tINkQ8YieZtDiNi5BAIhdkfhoZ2dGt1rNVvsAqj1YI2zND4eIpgwhHgGZ51cSRpKPVRU+SJSSUQj3St7KKg5Shaa/76ykZ+9Le3OazvGR7xXYfDU4j65IPQtCjb4gnCqGGrnEjzp/+P7t6f8sDD99L72h0c887D8O7dBFwF2CYeZXQomo+WQDlC7jGcQB2jjd1hfPYzol0s7TbF0klV+OOmDIjC7spp16r4DFPTVGpY2mq8YCRKKfqdhWwbu5wpJYOMJJqnROdwSwubHaqmDPmY4VQPQ9fQ7DaFPUUbStk8rBtkYuQjD97t6Shngyovo6UJGeHdrfv47n1vsnrdx1xVcidHBB6D2vlGst/9beRJENLE43Jy0ifOYNfRn+DX/3yTDS8/whEDK1n+7tMUvn2f4VIx9hCYdLyhsJUNbQRSEDJK3phl9k9OmFEXt6tZ7E1zXtykZamTE+cKwfno6QR2GQFOnFHHvp7+uBaCYAwRncE5OqPBcKR12G201hZRPQjr7nAJPm5GxKO4dhad3gC0Z/+xVlXoYdu+5CH/8x1R0HKItu4+fvPEWm54Zh1L3Wt4ofQ6fN1bYfE3YMm3c989RhBGgTK/i++ePIeNS6ZwzRPv8d0VG5hlW8cljWtZ0P4ijkcvg0cvg6qpMOUEIzJWzYzsv1GEAxSz3fkHk79MyBTWcOTT6ovpShL5L+68mnyyKPorjOfdcIPDDBGbTSVUfDMZPCGfaK4e3XlTIRfHDERxjKFiIn39bdA+iLSQBSNjLT14fFnezWccLHn05Nl/6RsIcPtLG/jVP9/D3rGV22seYv6eR8A7Ac7+B4yZn20RBSHnqC/x8pNTZ/ClJRO46vEGPvPqeDzO4/niDBvnlr5FyYbH4Kmfw79/BsVjjI7LlJOgcaEE1xFGD5vNcL91GvMwptcX403HtS6KJS2VGQlPnlG8JdC1J9tSpM2EyiQREgl3avM6/2KWlLNUhC1owogS1tBG+DBpPIumnjJiLt5KqdEdc51wxCgezEAUtCwyENA88uZmrnzsXTZu380VlU9yhu0u7Pv6YNF/Glaz4U6uFIT9nLHlfq48YxYXLZ3Ib/61lqtf2cSvmcTy6Uv58qeLmdL2LKz5G6z4I7z4OyhqMPIKzTgTqluzLb5wIGBJhTI+hZKQiBJfDnpQTDwq/8LyJaHE52LBuHKqiyTwUMbJsbGFwdDhb6TPmbsRBK0EFaeRuisHdbsPJw9jrpGFOXCioGWBgYDmoTc2cfUTa/l4206+Uvwsny95APe+bTBpORzzP1A+IdtiCkJeMbGqgF+eOYtvHjuJG59Zx+0vbeCB1zexaGIz5x9yFUtP8eJY+w9440547mp49ldQPR1mfBKmnQ7FaYY0FwQhjGUYe2lLFf2BPJmvlYDBRIMU0sem8tOEppRiT+n0bIuRNpnMg5bOcYSRQxS0UaS9p5+7V3zETc99SNvOLVxc/ByfLn4YT88OaFoMS240woYLgjBk6kq8fPeEVr5yZDO3v7SBPz67js/fsoKaIg9nzJ/BmcuXU+9oh7fuhVV/gce+D4/9wLj3pp8BrSdJ8ndBGALFvpFNSC3kLw7Tx3FgBPPhjSS2PNFIgknYh+JGnQ4TKgvo6OmnqVy8u0YaUdBGgbXb2vnTi+u5a8VHtPSu5oripzjM9zS2nj4jcelh35LQ+YKQYYq9Tr60ZAIXHDqOx1dv4/aXNnD1E+9x9RPvsWBcGSfPOo7jzz6Pkq6PYNVd8MZf4IH/gL993YgEOeMMmHi0BOcRBEEYJsFgLSOZsHwksQabyWWKvU7mN5VRVTgybrouh415TcN396ssdMNmqMnn+Z4jjChoI0Rbdx8Pvb6Zu1Z+xM6P3uE0xzP8y/MClWojBAph3vkw7wKompxtUQVhv8Zpt3HctBqOm1bDR7s6+esrH/PAa5u49J5VfP/+N1k0sYIjp5zFUZ/9KrXtqw0XyDf/Cm/fB95SaP2EMV9tzAIJLiIIgjAEHOazMyYBco4TVMvyxYIGhhdJrlPic3HyLJlWkAxR0DLI3s4+Hlu9lb+v2syWta9whH6Jn7tXMtG9Do1CNSyGGZdB68ngzo8Jp4KwPzGmzMd/HdXCfx7ZzFub2rj/tY384+2tfO++N/ke0FpbxFFTLuCIM7/J9K6V2N+6G16/A1b+EfxVRjS+5qNh/OFGBDtBEAQhJQ57flvQ8sSAJuxHiII2DAIBzVub2nj6vW28//ar+Dc/z3z1Nj+xv0OlY7eRkLF+AUy5ADX1FChuyLbIgiBgTPyeVl/MtPpiLls2hfe3t/PP1dt4fPVWrvnXWn79BBS4Hcwd+wUOPfgrHGV7hbE7n8K25iF47U9GUuzGg6HpUOO7Yb4MugiCICQgOAdN55kFLWjxyxcXR2H/QRS0QdDe3cvqd9fy4bp32fPxGhzb32b8wDrOsH1IhWoDB/T6anBOOAqaFqNajoPCkUnSJwhCZlBKMbGqkIlVhXxpyQR2d/TyzNodvLhuJy9+sIsfvbudH1GF13kmM+sv4LjijzhEv8LY3c/heurnKB0wFLaKFqiean6mGd9FdRLuShCEAx6lFGPL/dTngfudlaDBL59cHIX9A1HQrOx4D1b8Ed3XRXdXB/v2tdHV2U5/Vxu+7i2UD+xgvhogmDa6XzlpL5uAu+F4mHAojF2Eq2y8dMgEIY8p9bs4cWYdJ86sA2BHew8vrdvFS+t28frHe/jJWyX09C8FllLj7uWEso0sdL5Hc+ADqj54Ds+bd4cLc/qgtAlKxxnfZePCv0saJQCJIAgHDLPG5J9beMDU0GxiQRNGmQNWQdNas6ezj/W7Olm/s4P1OztxbHia8zfcSJd20qlddGsX3bjos3vZ6p3Kx2UNlNSMp65xIv6aiTjKJ1Jil7DCgrA/U1HgZtn0WpZNrwWgbyDAe1vbeXPjXl7/eA+vbanm7u0t7OnsA6CIDqY7N3GQbxMtzu00dm2jun01Je89jiPQHSpXKxsU1KCKG4wcbEX1hht0cUP4t79SBnwEQRCyhNNhBDcpy8VE8cJ+zX6roPUPBNi2r4fNe7vYtKc79L1pTxeb93azfmcHbd39EfvUFo/l3zX30lxdwKTqQlrMT6lfbkxBEAycdhutdUW01hVxxvwxgDHgs7Ojl7Xb2lm7rZ0Ptnewek8XT+ztYuOebna09wCaSvYwVm1lrNpGo20r9Xt2MmbfLuo2vkiV3oGb3ohj9Ssnba4q9rmr6XJX0+supcddRq+7nH5POX3ecgLeMrSrCOUuwO704HDYcdoUDrsNh13htBnfSoFCYVOGzqeUQmF8jyn14rBLhEpBEAQrBW4HS1uqKPTst91lIUfJixantaanP0B7Tz8dPf3s6+5nd2cvO9t72dnRy872HnZ19LKjvZedHT1s2dvNtn09MQkRC9wOaos91JZ4mTWmhLHlPsaW+2kq9zGmzIfHOTKJ/QRB2L9RSlFR4KaiwM3B48tj1vf0D7Blbzc7O3rZ29nH7s5e9nT2saGrjzc6e9nd2Udndx/27l0U9GylqG8rJX3bKO/fRnnPdqq6dlLFChrUPgpUdxwJDPq1jQ48xkd76cZJHw46cdCv7fThoA87/Ri/B7ARQFEzrQ6Hy2Fa65QRW3rWp2HsISN30gRBEPIAScAuZINRV9BeWreLG575gIGApj+g6R/Q9AcCob8HzGV9AwE6evoNpax3IGn2ebtNUeZ3Ue53UV7gYuGEcupLvNQWe6kt8VBnfhd55CYTBGH0cTvsjC33M7bcP+Qy+gYC9A0E2NvdyUD7dgL7tqM7tkPnTnR3G7q3A3r2oXrbcfR2UNrXgervhIF+CPShAv2oQD+2QBcq0IdN96MCA4DGvWm9cRCtAW18jz88I3UXBEEQBGFwjLqC1tHTz/qdndhtCodNmd82HDYbHmdwmQ2nXeF3O/C77Ma320FB6NtOmd9Nmd9FRYGLIo9TJnAKgrBf47TbcNpt4CqCoiJgQrZFEgRBEARhBFCDyUmhlNoOrB85cVJSAezI4vEHS77JCyLzaJBv8kL+yZxv8sL+K/NYrXXlaAiTbZRS+4B3si1HhsnHdpkKqVN+IHXKD6ROQyfh+3FQClq2UUqt0FrPy7Yc6ZJv8oLIPBrkm7yQfzLnm7wgMu8P7I/nQ+qUH0id8gOpU36QC3WSsF2CIAiCIAiCIAg5gihogiAIgiAIgiAIOUK+KWjXZVuAQZJv8oLIPBrkm7yQfzLnm7wgMu8P7I/nQ+qUH0id8gOpU36Q9Trl1Rw0QRAEQRAEQRCE/Zl8s6AJgiAIgiAIgiDst4iCJgiCIAiCIAiCkCOMuoKmlLpUKfWyUqpNKbVdKfWgUmpa1DY3KaV01OeFNMpeopRaqZTqVkp9oJT60ijKHC1v8PObJOU2JdjnuAzIfLFS6g1T5jal1PNKqeWW9UopdYVSapNSqksp9aRSamoa5Z6mlHpbKdVjfp8yXFlTyauUciqlfmau71BKbVZK/Vkp1ZiizKUJzu/kkZbZXJ9r7TiVvDnVhhMc71Kz/Gssy3KqLSeTN1fbcjKZzWU51ZZzDaXURUqpdWY9VyqlFmdbpkSo9N5nKe8ppVSpUupWpdRe83OrUqpkdGsTy1CfEblYH6VUrVLqZvM6dZvPqSWW9XlVL6WUXSn1P5Z7ZZ1S6odKKYdlm5yuk1LqMKXUA0qpjWY7Oy9qfUbkV0pNV0r92yxjo1Lq+0opNdp1Umm+s5RSbqXU1UqpHeZ2DyilGqK2aTSfNx3mdr9WSrlGu05xtv29uc03cqpOWutR/QCPAucD04DpwL3AFqDMss1NwGNAjeVTlqLccUAHcDUwBbgQ6ANOGyWZa6I+JwAaWJKk3CZzm2Oj9nVlQOaTgeOBiUAL8CPzfMww138b2AecZtbrL8AmoDBJmQuBfuBy8xxfbv69YCTlBYrN9nAmMAk4CHgaeBtwJClzqXl+W6POrz1DbTnVOc61dpxK3pxqw3GOdTCwDngduMayPKfacjJ5c7Utp3GOc6ot59LHvJZ9Zv2mmPVtBxqzLVsCedN5n6W8p4BHgLfMe2mh+fvBLNdtyM+IXKsPUAJ8ANxiPifGAUcCU/K1XsBlwC7gRIx3x0nAbuB7+VInYBnwY+B0oBM4L2r9sOUHisx78i9mGaebZX59tOtEmu8s4FqznkcDc4Angdcw31GAHVhlLp9jbrcJuDob18my3enAq8BG4BtR67Jap1G/QeOcnAJgADjRsuwm4KFBlvMz4L2oZdcDz4+GzHG2+QPwTopymjA6XfNG6VzvAr4IKGAzcLllndd8AHwxyf53Ao9FLfsncPtIyptgXat57qYn2X+puU3FaJzfaJlzvR2ncY5zpg1jvCTeBw43H4ZBhScn23IieRNsmxNtOZnM+dCWs/UBXgT+ELXsPeAn2ZYtTfkj3mfp3FMYiqgGFlm2OdRcNilL9RjyMyJH6/Nj4Nkk6/OuXsBDwM1Ry24OPlvyrU4YAzHnZfqaAF8G2gCvZZvvYigRajTrlGCbiHeWee/1Ap+2bDMGCADHmn8fb/49xrLNOUA3UJSNOgFjzXM6BfgQi4KWC3XKhTlohRiulrujlh+qlNqmlHpXKfUHpVRVinIWAv+IWvYoME8p5cyQrEESyQyAUqoA+BRGBzcd7jHr+qxS6vQMyWiVx66U+hTGi/g5jJG4GiznS2vdBTwFHJKkqETnONk+mZA3HkXmd9xrEMUK0yz/uFLq8IwIGUUSmXOyHac6x7nWhjFC3t6ttf5X1PJcbcuJ5I1HrrTlVDLnZFvOJqYry1xi6/kPMvxcHEGi32fp3FMLMTo91mfHsxgW02zVezjPiFyszyeAF5VSd5r33WtKqf+wuLnlY72eAQ5Xpmu2UqoVOAJ42Fyfj3Wykin5FwJPm/sGeRSowxgUzTbR76y5gJPIen8ErCayTqvN5UEeBdzm/qOKMtxqbwd+qLVeHWeTrNcpFxS0qzBMhs9blv0d+CyGOf/rGCbVJ5RS7iTl1ABbo5ZtBRxARcakNYgns5WzARfGyFAy2oFvAGdgmGMfB+5USp2TCSFNH+Z2oAf4HXCK1noVxrmC+OerhsQkOsfJ9kmbJPJGb+cC/g/DJeDjJEVuxhiJOg04FXgHeFxlcH5ICplzrh2ne47JkTZsynwhhlvmd+Oszrm2nELe6G1zoi2nIXPOteUcoQLDzWXEnoujQPT7LJ17qgbYrs0hYwDz9zayUO8MPCNyqj4m44GLMNwcj8W4Tj8FLjbX52O9fgbcCrytlOrDcO27WWv9W3N9PtbJSqbkT/TstB4jKyR4Z9VgWOF3RG0eXe/oOu0w98sfimbOAAAgAElEQVRGnf4fsENrfW2C9VmvkyP1JiOHUupKDNPuoVrrgeByrfUdls1WKaVWAuuB5cA9oytlJIlkjuJC4H6t9fZkZWmtd2A09CArlFIVwLeA2zIg7jvALAxT7enAzUqppRkod6SIK6/W+s3gBuaox20Y/vknJStMa/2OWWaQ55VSTcA3MXyoR1TmHG3HKc+xSU60YaXUJAxXn0O11n3DLW+kGYy8udKW05E5R9uyMEzSfJ/lNPn2jBgENmCF1vpS8+9XlVLNGAraNYl3y2nOxBjoORtDOZsFXKWUWqe1viGrkgkpGcw7K5cx+8HnYbS/nCVrFjSl1C+Bs4AjtNYfJNtWa70J+BhoTrLZFqA6alk1xsT/aA14SKQjs1JqFjCP9F3DonmR5PVMG611r9Z6rdZ6pfmQfw24BONcQfzztYXEJDrHyfbJhLxAhEl6BnCk1nrnEA6TsfMLqWWO2jbr7TgdeXOpDWO4EFQAbyml+pVS/cAS4CLzd7AN5EpbTipv0OKUY205LZmt5EJbzhGCo6Uj9lwcKZK8z9J5P2wBKi3udpi/qxj9emfiGZFL9QmyGSMQg5XVQDB6Xr5dJ4CfA7/QWt+htV6ltb4VuBIIKqH5WCcrmZI/0bPTeoxRJcU7awuGJ0G0Z0R0vaPrFPRAGO06LQVqgc2WZ8ZY4GdKqaBVMOt1yoqCppS6ivCLYU0a21cA9RgPrEQ8jxFBxcrRGCNQwx5VG4TMX8CIIvXPIR5qFsnrORxsGL6x6zAaT+h8KaU8wGISz/mCxOc42T7DISgv5pyVOzEeDodrrYfa+Efy/IJF5mhyoR3HIZ68udSG78OINDfL8lkB3GH+fpfcasup5O3NwbacUuboHXK0LY86WuteYCWj+1wcNineZ+m8H57HmL+60LLfQsDP6Nc7E8+IXKpPkGcxouZZacGwXEP+XScAH8aAhpUBwn3RfKyTlUzJ/zyw2Nw3SDBC4IcjIXgy0nhnrcSIZGutdwNG8A1rnaaoyDD1R2NMt1g5QqIn4rcYdbE+MzYBv8Rw44dcqNNwo4wM9gP8BiM6zRFEhmwuMNcXAL/AaLBNGJru8xijtdYwpbcAt1j+DoZ0/pV5Aj+P0bHIRHjypDJbtvMBe7FE8Ila/xPgccvf52KY+qdgPIi/Ycp8SQZk/inGQ6EJ4+X1E4xoM8eb679tynoqRhjXO4gNBfs4lkhkGBMj+4HvAJMxRr36yEyY/YTyYrji3ocRbWdO1DWwRjmKbhP/hTHRuhmYapapgVMz1JaTyZyL7Thpm8i1NpykHk8SG0I7Z9pyMnlztS2nkDnn2nIufTDctnrN+k3BmCvUDozNtmwJ5E35PkvznnoEI8R0MFT4KrIcZt8i21CeETlVH2C++Uy6HGN+3SfNOlycr/XCiAb7MYZrdBNwCrAd+L98qZP5PAx26juB75u/GzMlP8YUhC3mvtPMstoYuTD7CetE+u+sa81rexQwG/gX8UPSP2GuP8osc6TC7Ce9TnG2/5D4YfazVqds3KA6wecKc70XIwrKNoyX3nqMm3pMVDlPAk9GLVsCvIKhva4DvjQaMlu2Ox+j01eXoJybgA8tf5+L4cLQYd58K4BzMiTzTea56zHP5T8xQ4Oa6xVwBcYIeDfwb2BanAZ7U9Sy04E15rVZTeaUnYTyEg7lHu9zXqI2gTEP6j2gCyOc/NPAsgy25WQy52I7Ttomcq0NJ6nHk0R2vnKqLSeTN1fbcgqZc64t59oHI5jDh4RHTg/LtkxJZE35PkvznirFmI/SZn5uA0qyXT9TtqE8I3KuPhiKzOumzO8CX8USZj3f6oURMfRX5jOkCyMAyo8BT77UiXDKk+jPTZmUH2MQ9SmzjM3AD6zXfrTqRPrvLDdGDsidGArRg8S+IxoxUi10mtv9GnBn4zrF2f5DYhW0rNZJmQcQBEEQBEEQBEEQskwuhNkXBEEQBEEQBEEQEAVNEARBEARBEAQhZxAFTRAEQRAEQRAEIUcQBU0QBEEQBEEQBCFHEAVNEARBEARBEAQhRxAFTRAEQRAEQRAEIUcQBU0QBEEQBEEQBCFHEAVNEARBEARBEAQhRxAFTRAEQRAEQRAEIUcQBU0QBEEQBEEQBCFHEAVNEARBEARBEAQhRxAFTRCGiFKqRCl1hVJqTrZlEQRBEIRcQd6PgjA8REEThKFTAvwAkBeQIAiCIISR96MgDANR0ARBEARBEARBEHIEUdAEIQ5KqdOUUlopNTPOuieVUluAdeaiP5jbaqXUeeY2Sil1iVLqHaVUr1Jqs1LqGqVU0ShWQxAEQRAyirwfBWHkUVrrbMsgCDmHUsoBrAfu11pfZFk+GVgNfAnYBtwD/AR4wNzkfa31dqXUj4FLgd8ADwKtwP8ArwJLtNaB0aqLIAiCIGQKeT8KwsgjCpogJEApdQVwCVCnte4wl10JnA/UAdUYo4QXaq2vt+xXBmwGbtdan2dZfg5wK3Cy1jr4whIEQRCEvELej4IwsoiLoyAk5jrAB5wFoJTyAOcCt2itu5LsdzDgAm6LWn4H0A8sybyogiAIgjBqyPtREEYQUdAEIQFa603A/RjuGgCfBMqA36fYtcz83hxVXj+w07JeEARBEPIOeT8KwsgiCpogJOe3wFyl1Fzgi8DTWuu3U+yzy/yusS40/fbLLesFQRAEIV+R96MgjBCioAlCErTWTwBrgCuBRcDvLKt7zG9v1G4vAL3Ap6KWnwk4gCczLqggCIIgjCLyfhSEkcORbQEEIQ+4FrgK2AH81bJ8K4ZLxqeUUm8AHcA6rfVOpdT/AZcqpTqAh4EpwA+BZ4C/jabwgiAIgjBCyPtREEYAsaAJQmruMr9v0loHRwUxQwF/HigF/gm8DJxorr4c+BpwPPAQ8B3gFmC5hBAWBEEQ9hPk/SgII4CE2ReEFCilLsSY+NyitV6bbXkEQRAEIReQ96MgjAyioAlCApRSrcAEjJfPC1rrU7MskiAIgiBkHXk/CsLIIgqaICRAKfUkcAjwHHC2GVZYEARBEA5o5P0oCCOLKGiCIAiCIAiCIAg5ggQJEQRBEARBEARByBFEQRMEQRAEQRAEQcgRBpUHraKiQjc1NY2QKIIgCML+xsqVK3dorSuzLcdoIO9IQRAEIV2SvR8HpaA1NTWxYsWKzEglCIIg7PcopdZnW4bRQt6RgiAIQrokez+Ki6MgCIIgCIIgCEKOMCgLmiDkBIEA7NsEezZAbyc4XFBQDWXjwe7MtnSCIAiCIAjCAUJX7wD7uvuoKvJkrExR0IT8oKcd1vwN1jwI656C7r2x29jdUD8Hmo+G6Z+EksbRl1MQBEEQBEE4YPj3u9vo6Q9w8qz6jJUpCpqQ2+xeD89fA6/9GXrbobAOppwIdXOgtAlcBTDQA22bYcsb8OHT8Ph/w+P/Ay3HwmHfgoa52a6FIAiCIAiCsB/S0x/IeJmioAm5SecuePr/4KXrQGuYdhrMPRfGHAy2BFMnZ55pfO9eD6/eBi9fD9cfYex73E+hoGr05BcEQRAEQRAOGLTWKKUyUpYoaEJuERgwFKt//Qi622D2p2HpZVA8CLNx6Vg44nJY9FV47hp45kpY+084+r9h9mcTK3iCIAiCIAiCMAQGAhqHPTMKmvRUhdxhx3vwx+PhkW9B/Vz48rNw8m8Gp5xZcRfC4ZfCl5+Dmhnw4H/CbafAvq2ZlVsQBEEQBEE4oMmkq6MoaELW2dPRzaaH/5eB3x5C75Y1rJzzU/4551pe661nT2fv8A9Q0QznPggn/Ao2vAi/W2RY1ARBEARBEAQhA7y4bmfGyhIXR2HU2by3i8dXb+PZtTv4cMN6vtX1Kw63v86jA/P4bufn2P5cCTy3MrR9fYmX2Y0lHD6piiOnVFHicw3+oErBvPOhcSHcfT7cdhos/gYcfrm4PAqCEEIpZQeuAM4BaoHNwJ+AK7TW/VkUTRAEQchh9nVn7hUhCpowKvQNBHh41WZue2E9L3+4G4Blhe9zu76KAmcbb8/6AXWzP8ftbjug6OztZ8vebtbt6GDVxr28tG4XD72xGZfDxskz6zj3kCam1RcPXpCqyXDhE/DwN+HpX8D2NXDqdeDyZ7bCgiDkK98GLgbOBVYBM4CbgR7gf7IolyDkJVprAhq2tnVT4nPic0nXUxBSIXeJMKK0dfdxx0sb+OOzH7J5bzfjKvx8/ahmPsXfqXj2ClTZODj9XlprZ8TsO6Mh/DsQ0Ly5aS9/WfER97yykbtWfszcsaVcclQLhzZXDE4opxdOuhqqp8Kjl8GNx8JZd0BxQ+p9BUHY3zkEeFBr/aD594dKqQeABVmUSRDylhfX7WJrWzcAboeN46bVZlkiQch9REETRoTe/gB/enE9Vz3+Hns6+zh4fBk//MQ0Dp9Ygu2Rb8IrN0PL8Yb1ylOUsjybTTGjoYQZDSV889jJ3L3yY258Zh3n3PAiS1oq+c7xk5lSm7qcEErBwV+G8olw1/lw/dHwmXugasowai0Iwn7AM8BFSqnJWus1SqlW4AjgJ1mWSxDykqByBiOTL0oQcoVMhdgHCRIijACvbNjNiVc/w/978G2m1hXxwH8s4o4vLOTIJhe2204xlLPFX4dP/Tkt5SyaYq+TCw4dxxPfWMLly6bw6obdLPv101x6zyrauvsGV1jz0fC5v4MOwI3HwUcvDVoeQRD2K34G3Aq8rZTqA94CbtZa/zbexkqpLyilViilVmzfvn005RQEQRDSoKd/gPtf2xgxWDASOG2ioAk5SN9AgP/9+xpOu/Y52rr7+MNn53HbBQuY0VAC+7bAH5fDxy/DqdfDkd8fdnAOt8POhYeN56lvHc75h4zjzpc3cMyVT/HEmkGG0a+ZBhc8Cr4yuOVkeE8iPArCAcyZwGeBs4E55u+LlFIXxNtYa32d1nqe1npeZWXlKIopCIIgpMPeLmPw/v3t7SNSfmOZD4Cx5ZmLZyAKmpARtu3r5szfP89vn3yfM+aO4bGvLeHo1mrD3LtrnTHPa/eHcPZfYMYnM3rsEp+L75/Yyr0XLaLI6+BzN63ga3e+Froh06K0CT73D8Pl8Y6z4N1/ZFRGQRDyhp8Dv9Ba36G1XqW1vhW4Erh0xI7Y1wXrnoL+DKQVGSnat0HbpmxLIQj7Dz3txn2Vh6zb0ZGZNEijhR7Z4m2ma2MGPRxFQROGz+rNbXzimmdZvXkfV581m5+dPoMCtzm9cef7hutg1x449wGYcPiIyTFzTAkPfuVQvnrERO5/fRPLf/00r2zYnX4BBZVGvrSqVrjzHMmVJggHJj5gIGrZACP5vty+xuio7VmfuTL3fgwDGcwKsO4pWP9c5soThAOdd/9u3Fd5yBsf7+Hf74pLd5Cg/qczqAiKgiYMi8dXb+X0a59jQGvu+tJCTpxZF165d6PhMhjog/MfgYZ5Iy6P22Hna8dM4i9fXIjWcMbvnufaJ98nEEjzrvGWwGfuhcoWuOPT8P6/RlZgQRByjQeB7yilliulmpRSpwBfA+4dsSMGTH3QlqG4XV27YcMLsOnVzJQnCDnI2m3tdPdFj6UIBwLdfQPs7RxkzIE8QxQ0Ycjc+fIGPn/LCsZXFnD/xYdG5iXr2AG3fsKwnJ3zV6huHVXZ5o4t5eH/XMwxU6v52d/XcP5NL6dvjveVwWcfgLIJcPtZeTvCJQjCkPgKcDfwW2A18H/AH4DLR+yIA2ZHI1MKWtBVsq8zM+Ud4Kze3MbmvV3ZFmO/IFNR7tq6+3hr015Wrh+El4yw3/DEmm08+e7g3UMVGfRBHGFEQROGxL2vfsx37lnFYc2V3PnFg6kp9oRX9uyD206DPRvg7DuhbnZWZCz2OvnN2XP44Sem8dz7Ozjh6md4c+Pe9Hb2lRkumaVN8OczxbVHEA4QtNb7tNb/pbUeq7X2aq3Ha60v01qPXPivgOmKaHdmqEDTYyCTEyIOYN7duo+X1u3KthiCBW1G6+8bkLD9o43OpB/fEMm16x48JzqDk91EQRMGzcOrNvP1v7zOwePK+f1n5uJzWUZ9AwG454uwZRWccQs0LcqeoBijdeccPJa/fHEh/QOa0659jr+u/Di9nf0VhpJWVA9//hRsfWtkhRUE4cAkYFrQlD0z5YU6UCOsoK26W9woh4LWRvCsQG51MkeDTLfI7KsKBx4D6U4ZySFyQuL2bdCxM+3NRUETBsXjq7fy1dtfZU5jKdefOw+PM6pD8eSP4Z2/wbE/hpZjsyNkHGY3lvLQVw9ldmMJX7/rdb5335v0ppMws6DKSGDt8oWtgoIgCMOhrxs++Df09xh/B80BGetGBC1oo/CK3/n+0Pbr687sjPp8Ys8G2LjSCA5zgCFG3fwnD/WzUSPpI23dU/BB+nENREET0mbVx3u56E+v0FpXxI3nz8fvjpov8da98NTPYfY5sOCL2REyCRUFbm67YAEXLh7HrS+s51PXPc+WvWl4LZU0GvPoejvh1lOhU1xdBEEYBjvfg47tsOuDkSk/qPDlam+4rwvWPHTgeiUMmHMEB3qyK0c+oXVmLI79vYbV9wC0XmaKQB4OrOgR9voeiTMiCpqQFtvaurnwlhVUFLi58bz5FHmi5kpseRPuuwjGLIDlV+Zsx8Bht3H58lauOXs2a7bs44Srn0lvbkH1VDjrdmPk8/azwiPfgiAIgyUYFMTuGpnyR8vFcaj0mwNj+zZnVw5h1BlykIYPn4a37rEWNDS2vGFYffd+NMQChDzUz/ISUdCElHT3DfCFW1eyt6uP6z47l4oCd+QGvR1w13ngLoIzbgWHO245ucQJM+q47+JFFHkcnP2HF/jzi2m4LjYtgk/8Fj56AR66RJ5SgiAk5eUPd7F2W3vsiqCC1rnTmMcVzFeWsWfKEF0c+7qMEP2BgDHoNjBSYaxHWHEMBA4oC0kuBG0I0tsfoKMncf69tMduO3bAjvfCf2cqoXMwpUWODiLnAwM51N5yhZE4JaKgCUnRWnPZPat47aM9/PLMmUytK47d6JFvwc61cOp1UFg9+kIOkZbqQu69eBGLJlZw2b2r+N59b6aODDT9dFjybXjtT/Dc1aMjqCAIecmmPV28tSlO5NhgUJDgnNbeOErcIHjynW288fGe8IKh+vO88zCsfRz2bjDmR219M7K8TBOn3K7egeEHIVjzEKx5cHhljAYZUCTX7ejggdc35Uw+sCff2cY/V28dfkEfPAmbXx9+OTHkuHU5Dwi6ONpEyU2fwODvT1HQhKTc/NyH3PPqRr52dAvHTauN3WDV3fDqbbD4azB+yegLOEyKvU5uPG8+XzhsPLe+sJ7P3PAiuzpS5Etb8h1oPRke+z688/fREVQQhP2Hjh3D2z9o6TLZ29XHuh0d4fWhoCOD7EAFFaZgPrY+M/fXEDoXQ+Ufb2/hlfc+Hp71bqB3BK1/GSB4nnevgw+eGFZR63ca1/1fa7ZlPidYf0/YupsmXSkUxax36UPzM6X7O1RGfYrrno8yNl912CIP9BnxFvZtiVqRYlBpCM8jaaFCQt7cuJcfP7yGIydX8ZUjJsZusGud4erXcBAsvXT0BcwQ9v/P3pvHyXGV58LPqarep2d6enaNdmuxFkuWN2zwBjEY7BiDjU1wEgI3hIQtIZfk8nFJcrkhCeEGQiBsJkAIIQZDDDY2YBvvxpZkydqsfZdm75npnu7pvbvqfH+c2utUdbc0kmypnt9PmpnqqnNOnVr6fc/zvs8rEPzvW1bhn+9ej20nZ/D2r/4G+8dz7gcIAvCObwID64AH/hCY2Hv2BuvDh4/XNJ45kMLx1IzLp00yRxrT5YrTzIgX1TB1LVeMzrGD1mBc5NCvmMrlhYCS273QHDRfryorGM7McWHyfQ8zJmsOcc5JlzlUi6jUZUzOnuf56JMHHc6RVuvrrBV9HtoMpPadVhNzVp+sMssWrLToAns/bt0ovoPmY46Qr9TxsR9uRzIWxD/dtR7E/jJTFCYKAgB3fnsOC6yeO9xx2Xz8+I+vQbWu4I6vv4hHd9tXSEwIRoHf+SEQbAN++O6Walv48OHjwkW2VMNU4TTZHZMVwM0/Ol0jVDtOY840Jm3OYR275VzKp+e4XCg4YzWptBX/8+06zCGDtvHINF48MvWqygGcc4zvYs7RBZTT2RRauOQTuTJ+uXMI9RaLa/sOmg8u/uah3TgxXcC//M6lSMY4SmMv3QucfBF46z8CnYvO/gDPEC5dkMDDH7sWy/vi+JMfvIwvP3EIitsXYMcg8J77gNkJ4IH/cVbDgHz48HEe4hQMvTrv/aTX1zpFB80+juPPn1o75xpzYDi/2o3vMyZ5fsaUiueYdWn19E81/JeDXJmFf57pW0RRqNUOKXtE+JyxQRiLSlP51y5r6CAbWm+Au1m7B3hM3aGJPAitNwz/tcN30Hw48NNtw/jpthF87E3LcfXSLucO00eAJ/4vsPxm4NJ7zv4AzzD62sO4/4NX444Ng/jSEwfx0R9uQ7HqEoc/eDlw6xdYGMjTf39Wx+nDhw8fXAZFY7yaiGzIV+o4Oe0SGqdZHTxj/bSsUm8jp1k0FMaYEwet+X2rdQWzZSc7WpeVM+bonbmaVGem3XMe4ng2i7jPER55ZQyP71WFVyYPAocen9t6rJkTqpqsB7OvfnZyuog9o8xBbBg2mB2xKnG+GlHOAft/AdSaqIkLwHh3tfZ8CEq95SfqtXOH+jgrGM4U8TcP7cFVi5P8vDNFZqGNUhC47cuvhrftGUE4IOKLd6/Hp29ZhUd3j+POb2x0j++/7L3s3/NfBPb/8uwO1IcPH68u1MqnwT7MEYMW62E/hcYO2vMHJ7F9KHNumCJ7n9U8+se8cusMlGsyHtszjoMTs14dnPrYTqGFFw5P4an9Tjn4X7wyhm0nzaGCrNW6omDrifRp5Y6dqQjHM4VzrjbZSvhvrQTsfqChM3SmLwGlFJW6Om9FNZ2iWnA/oFWM7WA/vd5bKoO2d4yjSuuGkxvPkBKngdN+b00dYtc5N+K9n1wDTm42nNgW+iUEp6Ss4jtoPnRQSvHJB3aBUoov3r0eksi5PTZ9g9UBe9v/A9o5qo7nEQgh+KPrl+K777sSw5kibv/qC+5Frd/2T8DApcDP/oQxjD58+Lgwsf8RYN/DFsNh/3gOD+0YOSNOEI9BkxWKHIfJ4aGq5kWM58wryLY2eQW1OecylC7ioR0jp5wXRaePQJTLavPebWglUY7w6sy10iel2DOaRanKdxxaYai85pznhFVr7BwOncY5nDEG7TTbPT5VwLRLKFzDcjaOAxqwG63kR9EW9p0dY/OQPsr9WOdSzuDihnZfEqU1Nc2WoDkdXs6DXEe5JqNSPwu5aLMTQLk5R7DZqXfdr1l/KX2UFTefOsBv39RPKle2MOkEAAFt2ZP3HTQfOn6w+SReODyN/33rKixIRp07TB0CnvossOJtwLp3n/0BniPcuLIXD37kDeiIBtyLWgfCwN3fZwqPP34vUJ1jNS0fPny8pmD2UbRi1WdC0MHRplzD0PAJHJyYRaHSvBiJ6+ITACQWsp8NwsL2jbHQp2pDI85tHmjDPTQopSyS09tQkz0YmSast2yphsOpvKtEvbkJWaFzY4zPoUHvuP5zIVgl13G6vNDO4Rn85jC/nETLz8HwFv1XqljDRQPlaWDPT/VC1opCcXyq4HGdbNsreXfmSHP8BNFzeC3PVCXPQgo5OJzK49dqOGOpKuPxveMIlacwb/Qxa7HuOY5eypVq2Hx0GrtHXByjVhzbmSEgN3rqgzn+PHDo103tOldPUlVWMJHzWAjQ7ydOiGMxDaFmMJobj05zmHTKQkJbePZ9B80HABZX/Llf7sN1y7txz1ULnTvooY1h4LZ/OW9DG91wUU8bfvbhBkWtOxcBd3ybSdI+8vEznznsw4ePVy3MzEaknEL35MbG4WinJBJivIcopcDQSyiqq+6tqoY5x2H/adnJsUU7v+a/HmxtmM6fxwwVKnU8d3AS1boC6eQLiJTGINa9FCZNbZQy3FA1rRuZUhbONnnQ1oLRxiO7RrF3bO4EGk6qrBoB2ALoK//dct0xM0LlSeDo00Bqv8E61Sssx6bUZI20/CSw90GrMzDHaPk2NwlUPL53HI/tmdDvsUBFvabqeI9OFbBzeAbHG+VVajj4KCsncITVozs+VTCeG421IqIRYjgXKEzyx5Q5gUPHjus579pCR1A7R/txc4iDqVlMzZZxZNKNzW3hog1tBk68CMDjHTR95LTDNGP546zkSAtwvpvYhleGZ7Dp6DQqdRn5Sp2jO+D+rsKRp9Bx0iM0+xTNZd9B8wFFofjL/94JkRB8/s51fJWbjV8Dhl8CbvknIN5/9gf5KoBW1PqPvYpaL7+J1YTbdT+w5dvnZqA+fPg456AUCFamIdXySE69jFAlDTrXYUqUWtgISoFyPq0bF4QwiefxrPvKcCTA2AGuWq+5YfYLZ5sBolSbW2l3sdCpWQnXtIuiUBSrdRycmEWmWMV4tgyqCaF4eYPmfg4/qRvhljETFj4WyR5h+4/v8hzqULq1kgNejFu+Yrofpg4yp1R2YXNqJSA77NmXVFedkondLNQWAPIT7NhJFpqVK9e8QwwLqmN2Bp2BZmtSDaWLLGzUxNyWa3VU6rKrk6c5Na7nqMvt2RooppGaLWPn8IwugqHV/xvNVfHo7nFkS3xGWlaoN/viHIT1T63O2PAW9Ey+qG/2JKzPyAKwR5un0F+lLmPH8AwO2/NE5Towuh04+iwopa7hxV4Q6yUkZvbwnbzCNHvWTWqXrqNX3x/aO1NRgCf3TegsJvKTzJl05C7yWzTbhJbn+xQul++g+cB/bDyOzcfS+OvfXo15iYhzh8kDwFN/B1z828Ald5318b2aIAoEn7plFb70bo+i1tf/JbD8LcCjnwKGtvAb8uHDx3kNhVL0TG5C38SzRlkx1ZmiLS6pjmVL/JVoSlGXWdiMVCugXJexf8IwWAiATUwFHpoAACAASURBVEensfmYe9hbIsocs86oh4MGnlHrtDj6hh9DcnqbRzvO8XP7AWA+292jWfx674RufFOYQw29LJ/mrKL23EEIE7uaYklEobVr16xdW6zWse1kBsMZFwfwxIvAyU3eSnt25EYNK18dyNP7U97hrGdMXt+AJ5NczgKj21nI2WwZG49Mw0xBEJcJrcqKu9qyGdoCQn6cqQyaUJOp+tPKoE0V2d9u7e8eyWLT0Wlki97XRlEo61NdXJA19ntyP5fdPaNxSorCyd07tWfJLcdWy1ebyLqEnNbLOJTK4/G94yhUWlu86sjuM0ZlarsmK8iPH2bzWeSH2PLhcn7HnmXOpGN3/v7mPNSiek7mgt7DmRIy9oV9F/gO2gWOY1MFfP7R/Xjjyh7cdcV85w5yHXjwQ6ww863/fMGFNrrhnRtYUeuazClqLQjAO+8F2ucBP/kDv4i1Dx8XOLS3ptJAzGDXcAZPH7CGluXKNbx0LI2dw7yCwYxBi88eRt/EM9h5eAh1pbV3ND8fyOaQNeFklKoy6gpFpDzRRK/WBilVHS4X9i2VY05D3cYWAu4Gu2WnBiCUGVKzal0rs5NCKSDWiwhU2fzztLM8QanOxJg2WvsnBCVVMCTlxsTIqlFXdRcUoYRYDeETLzIGDQCokbvFq2MlKxRj2ZIhiJFv5jqqOPRr4OizrgwTqIJI0chJ8hQ2Of6CRWirLbPPVizbNndqWy8emTZYDy9o99jkAeDkRlBKdUNaW0AhpkLtdVlBSi0sL7rYPxpTUvHIh5ycreCRHSeRO/gckNqHqqxg+9CMwbzNnHAcY49mSpsdwNO1xY49Axz8lXWbOpet5lkemsibDze1x36kZ0v4+c5R5weg+rPdao0wc1MzxYr+3Gw5lsbLJ9MtnIN1Hseybgw5/+QMRtrZ36T6nBHCREIoZWJMzx1qjp32HbQLGLJC8Zc/2YmgKOBzd7iFNv4rMPIycMsXgHjf2R/kqxiXLkjg5x91KWodTTLRkMIU8NMP+EWsffi4wGA2QgWdQfN+D4xni1BSByz5QnV1Vb9Q4RxLKRRKEVJzVOrlgs1wM8ZwdDLPDfuiulHmNTLTh5kTwMg2xwEvmAQhmrfvGPu3ddtW/HzHkNVBa9AGNRl5LUNRgMxxgFLL6rbRuCmvDxT940+jN/UCAEBo0TDOH3sJgyOPNrEnUftTUa9aJ1KraeepaMgZW/qY+gszEEEV3WGklOKhHSN4+UQGj+waxUvH0gaT0cp3VjmL3PQonjnAz1uLzx5BMr0d4RJbyKQK8Mpw1mAbpo+wUDJAv39LKlsVyx22sYb8RQO7QZ7KVRyszK9eGcPxKWu43XiujL3jORQqdSiUIlIYQWx6t96XOZetIXvqMaZsiTnYGsumlRvIFKvazrqiqv1Yoja8Y4g5qqnZMsot5MRRWyg0AMYw1azOiNYP9/n1eKjj2YOIZw+6fk7U++2V4SxjwV3CTGfLNW8V7El+H88dGMfGo2whPK3OZ9Pqpur9pjn6r7iKpPDbe3p/ShdHskMTh9Ke7FajRH0H7QLGd39zDFtPZPCZt69Bf0fYuUNqP/D0PwCrbgPW3nn2B/gagF7U+jJW1Poj95mKWs+7FHjb51ks9HP/dG4H6sOHj7MKsz2khc41Mho6svtZ6M7h5mqB8bN5+EbkKyNZ7Bp2Gh8yb0z2bWbHaXgLV3a8wAv/KkwxR8Or/dwoyNh2dGQPgJomzWuuilXZkKZ3hFXJJuEUlzamDgDDW4EZTZHXOmep2ZJh0M4MWT5LZHZjaMvP1dA7PnTjevoIDu43cto2HXU/RvP7KKVszvb93MhNsjTubphTCO7uKmX3ysDoE7rDqJ3icIYxhGK9ZBGdaQVe9c203DhBYfdCvlrH0ak8NmlzOLqdhZKZoF1f+/kQ+4b0Yaszo87jdKHiUNKryoqDodRY07qiQKFAMrMDkdxRyzHa/UGMiwQoCsu5NG23+0CP7BrTnVY2RNMO6q+6ES4GLOqnlPKZrJqs4GS6aMydCbJCuSzm5mNpPLLLRVXR4ohT0/92uDsYbbmDaJ89BDq+y/Lusi+iHJ3K48D4LLeH8WwZT+1PIT28n98JwPJDK1YG2T5iweVaaDgV3lErL7BzKGOUyzBNRlVWMOPCHhvlNSgUULi+kzjwHbQLFIdTefzT4wdw06o+vHPDoHMHLbQxFAdu/ZIf2uiBcEDEF+9aj7+6dRUe22Mran35+4D17wGe+ccWjC4fPny81iHLzi9iamMlsqUqUrOGwajVAKvUZWuBVzfLSA1bExSXvCGO82KHZshQ6jTUvPunOJku6MyAGbqRf/QZ4IjHe49SpGYYoyEoNdcQRzOihZOQ9xnKbcQ21kd3jxtS4aZx7xjKGHNdV3/KVTxzMAXdAAfLG3np6DT2jLI2SGqvtf/8cUxMjCOVc1eg+/nOUWYom3NXaHNCEpRSI3emkGLMUoXNUU1WUD32om5UP7TDvbhuXVEwnClCoRTThQpeODyJck2GQPmGZG/qBfSPP+05tnShimpdwZ6TKSg2NrY5doAY5wjjLsuWqq6hZc52tWMpiFKFoFQx7ZLTw3XyqX3cRlijFoJsOGJsANRs/1QLTO1zz08xMGKVgrcvlyiUOUyFSt2h/qnvaxRTMyJw9K4pAtWs7TgGXj2yHUMZPHMg5XjOtfvO7vCVanXIpgWUYHUGUm3WZd4odznIPGYydRCp1JjBCjpGDVepeY1NzfMiBcyoWdU5KYCBsaf066pHK9j6MJ/7dL6Caf2929i23T2axYtHJlFTKI5Nac99c47WtpMz+v3kM2g+GqIuK/jET3YiGhTxD3es5Yc2vvhlYHQbC21s6zn7g3yNgRCCD1y3FP/+/qswnCni7V99AZuPTjPH9tZ/BnpXAQ98oKEKlw8fPs4P8JgI2ZajciiVx8m0Uw78lZEsdm5/CUPpIki9gsGRXyKcO+7shLJV7UBNdXIIgcMYAgAqI1iZ5toUmuEynStg90iWGTYOAQ6+wZaarXCLLD+1P2WIJ3lIaU/OViy5ddQ+djXsTfuKIkoNnZlXINRNYWe1PHI2J9HIVWM/ZYWirlA214oMzSjTDHKzAV5TWD5JXmVWqMNpZPuKcoVFmbhYXUOO62oO36SWQraUmmRjqGKEngWijFk6+BgA4NDELHYNz4AWXXJsiHE9943NYjxXxnShoub5UEfIn9MQd7Eg5Tqy6Sk8f2gSv3plGKVdD2Js/6YGbbnDvuuhVB4jMyVuYWuvMWpsmmddtcqsjQWlKNWMedDWUQRC9GtNTPuaW6aU6s6yGUSuQKwXXA1wQzjCi/GmFjabUgohtRu9qd9Aqhl9anvEZ52hgNN59hxoeV0AMJOb1UtRlGvGPSgrCvaM5rDzuMEyJmb2oG/iOff1IM52e1jmyXTRIdXvYD3Vs9DuT8BgvhreRhwRG0JlBGrsfSPVCyCKbLlvUrkyXj6RQSx/AlJpEru2Po9jz36fhTo3UGU0nZzj7xmHI8o7jLIcNNp6DUXfQbsA8Y1njmDn0Aw+e/ta9MY5oY0jL7PQxtXvANbecfYH+BrGDSt68NBH3oBENIDf/fZm/NfmE0xg5e7/ZHH0P3kfP+THhw8fr32ozExdVlDkFIl2+34eShctRiMA1BSK3UOTujhENOc0yChVLGZFRzSAaqiTfQZBDxnszLyCnslNIDWns6QdX85nUK7LKFdlOIwVzsB3cUVLDBwwMwYHH3ewSYBm3KmMCCGWfiiAzO5fY3pyTN8WPPiwo59keju2b+IzP+VaHQ/tGMFRs8FIKWYrdWw9kUa6oBl71kXKjpl9CBW0xTT+RevI7mNy9mpBXo1J6Bt7Gn3jzzj2F2wlFg6YpMcpNTmh9bLhoGl5ZyqKahhhtVxwcUoMPlFjUShlTg6himMx1shJ82AuCQGGNgGHHweoDFG9H4VZd/bOCTYqLVfSJQVJLWztzWjwRGFY4Bg7zsEsHXwMGNoM+fDTiBaGQKAYMvowMWgwHHZBAPd72tjTiu7hJ9A//oyric977rWFDeLCoCm1Moi6QCGqoZSxvCEkEqyZWGLbYtC2k0YO68HfPID+cVZeYnLWcG60rjJ55wIRtwwCVbiLLWbhnqm8m21jf58oxnhU5l5z0GSFYu9oFhO5Mv8el/l9iPUSoMjoG38W0dKo5ZbW5iMxsxvtYxsRK6ihzaaoAd59Va0r+nsunneGdT97sDmxDy0HjRNU4QnfQbvAsHskiy8/eQi3rZ+H29bPc+5QmQX++w+Btn5WkNpHy1hqKmr96Z/txl89+ApqnUuB27/K8jd+/dfneog+fPg4E1AN6x3DM9hzyOlQTc3yw7gmZss4nHIaP4JSwwGViSqV8qyemRrednwqj1/sGoWUZUZbSBKZQUMpFCEEAgVkdgREqUOqqcYgR6JdM1ADplV6s0VZqsqGHDigF3E9kTbGm8qVvZe+Kzlu8n+uXDMZRgTHJk1zoABHpvLYepg5aLH8cdfmY4UTXFELjTEywpIAgGJiVmMa+CGHkfIE4pOsXAB1YWciJU25l32u5ZdJchFS3XktB8aecB1/rlxDRlUKbB9/0QjBtHRtOAbpXIGbO0hBoCj84sBa/pd1f4qB0ScwMGoaG6/4VoGFXBKqgKhFoymRMJQuNmQRzGGY0eIwQBV97D2jT7Ei0Q3AYx5khSKsKoaaPz8xzWdsaX4SnZldDkPcfHktKqvDW5iQjGUc4KZ7ENUbMI9D4dw3hLJ9zOx6tlRT8/esbhHZ/wiIKhZE1WsiKhXnc6aGW7pBv+6UYvtQho3RfJ6cdwLZ/YAh2qJheAvEQ49CMDlIlAI1k0M8lHEpDg4KqTZrCImYnOLuKVaKSAtNzJVrKNZkDGWKeP7QJPLTRu5cVVaw9eiENd9RY0BpHVBkvR0rGwk9X7BUk4173MSm88LEpwsVC0NoPyc3JDK7LYs0gTp7t8ot5nf6DtoFhHJNxv/88Q4kY0F89vY1/J1+8RdM7vXObwORzrM7wPMI5qLWP9h0khW1XnwLcPWHgc3fBHa7v1B9+PDx2ke47FS0O5IynCB7aCPXCK1V9BAgQhUWDqg6IlOFKgAFoQnmSAhENTapYehVijkk09tNtbDqurFdrsnYPZJ18avYxrqi4PG945Zaj/vHc9g7lmMhfirGc2U4DRZ+WKT5s0Ihr0vcA4YsNaCFGhqHJWZMghm8QRfcax5ZVuJPvIhI9jAbd9ZpUBohm1oeUgOjiohI5cqWsbshXHKXgZ/Q2A0KI8/G3LfJMdgzOgNFYU7r4PAvWPiqus+ukRnssLGb5ZoCqV7g5OUAAq1Z8tKOpGs2Q1LLz2PhsxqboxAB205mdBaBUg8n2tSvKFf0cUj1Ajdkzf4s2Fwq9j8FOjNMgKXWBDVh1uW0bDfnw+khjsQSyuhZygFmgRem0pgpVC0qi+ajJ/MVXY1RQ6FSBxTF4qLVFAUV1TkIVUyCIKbGMpNj2D+es56DCeb8Vs1RK1ZlS8F2O7OrI8cY5NGZks7uU1CWK2pCzcXpkBXFKNRMKRIze9E+ewhiOYNcuYrtQxnUFEU/N4PdNe7zbKmG5w8b5z6dryBXrNgWXIzzyBzfqTvc9ntdUsM8SzVZZ1tPTs/q78ZgJQM7eGszehkRuaYvVtgRK5zQF2mClTQSw8+gbfaYs+xcA/gO2gWEL/36IA5O5PH5d63Ti5NasOvHwK4fATd8Elh0zdkf4HkGXlHrfWs/Acy/Cvj5x1wlY3348PHaR1v+mGMbMZmJZuMJ4K/HEjU0TUOwMA4odZ0hYSvyzKAkhKhGiREvd2K6iFBlWs+xCmePMuGO3Ci2ncjgyGTeMKKMQeoGtSZ0ksmXgVC7Zbfe1G8azADLuRjPlQ2Df/cDugqbtjLdkdVU24hF8MMwjihfIdIF5hV+zdQzh2FlUiOWUC8z7NLlBydmdbEQVxCiS3ybER1/ybGta3orUM7Ba/WdAkYYl3rt85U6XjSp9hGqQJZraM8dAgD0TKr5YBxHoliVdcNfc1T10gIuKoFpu+gGK+QEQg3JdGoPlwS1OtEuEJQKKGWF1d1mwVzsV0O2VMXWE2k9n8nsxGUKFbTPHkKkYAq7tDNlLkyo2ZAX1XprhIBbb44b+mfCkck8njmYwnOHJnU1Ras0v8fxtoWAvaM5Ry4XAFBTc3uHJpGv1LmS+7JCLUqj2nukVJMtdeUIx0GjlAJEQE1WMJotWUJCQ5UpJDK79b/d8v+OTRUwlmXvuGhxBKEKW0ARKxlM7XsBsmKV/teeSccyj43RFWjdooipXZNALYcj+7dbQnvNodSimrcqCyHdKTs+mdPfw5SIjnPYepxf0H1kpoipfMXEorujZ3IjAMas+wyaDy5eOpbGt54/intetxBvXNnr3GFiL/Dwx4GF1wDX/cXZH+B5jHdumI+fqEWt7/zWVjy97v8BUgj48Xs9E+h9+PBxfkFTaeSm2bgyWcYHHZNbgPQRPXwnXE5Bi7oSCDOWCFVATV/thMp67o9UVQ2t4S2OEDkrS2A1fggoIDgNmEYnkC5WMZwpYnSGnXdVVpCaTgOUYnTGGu5pN/gtdeTkxuyUlk/Sm3pe36Q5fOa2jkzlLQ4bYBivdvtp//gsNzTQ2i/f6Arkx7jb3XJo9OYA43tBbTtdqFpW6zuy+yDsfdDRt13RErDK39tZBbL/Efcx2KDKquif0hYSaszj6k29gHRqBFEtD8ixM3EIzyiUYiTD7pfk9FYQpWphN2rqH8nMDghyBYFqlgnrlFIoVOrcfCZtLrRrvn88h2MTBosyli0xh5CdLfQf2r2iqRqa5jR44hn9Omn1CyVB0J1J/fnngcp6N/HcYffdTP0FtOeZcymcNQ/Z31Vbjh5P1XMoXQKIYJmzw6lZTM5WkJjZzUKKtflzuQ3MdRvN+VvB2RFIFafjY3GsTLCzl8R2z2vsKbGVn5ApRUVWdLZSZ37FoO705UsVQ/FVA6XomNmLrqmtlsUeM8ayZRyfLjjGYi+BoYm7aOy65ZEpTDlfODb4DtoFgEKljr/4yU4s6Izi07escu5QygA/ugcItQHv+ndAlM7+IM9zrF+QwMMfvRYr+uJ4/09H8cCS/ws6uR945M+9czd8+PBx3qBr+uUWj7AyaAqlmElP6uFAHdm9jDADS7JnBpXBoNkhaCIhcg2KbF91V99DJgbNMAbZijo3P8kEM1tATKIHiqpgtmt4Bi8PzTDRCsfRHAELMLU6r/wtHWrop8UIbvRutYVcmvcmBI5QO6iKbPZ+B0YeR3t2P3onnkdDNPO+1/KCTNc+ULc7LVZGVj3A0ZSZIXXYgxzHV1QqliHWFMZAEkLYvagb5qdWLw0AyqkjLqPlo1Cp6wIpgXoegVreVTVyYOwJnb0Ol1PYN57DUKaIUZuMf7GqOgTmUZgu7siMM1+0plBsPzGNfKVueTa0pyJYnUHfxPMAlXFyZARivYhKXcbLJ5jj58Y6K5SiXK3pixbtuQOuc1E3iQnFsmy/vWM5R5mCSqWCROYV49TU4WqOm0FQO6/jTKmK1GwVj+0ZN22rIWVinrXQZKXKz6t1vbpU1mvP8WB2CsPFMbTn9mO6UMHWE2nUZQpCZRwyhYprkv52B208W8bhiVlTTqLRrvb2IVQGATUiD8BEh9ryxxAuT2BgzFpGodE59kxussxn38RztnNjnwWqMyySYWI3vOA7aBcA/v6X+zCUKeKLd69HLGRzvhSZiYJkh5nSYPvAuRnkBYDe9jB+9MGrcedl8/GJl5N4uPN9wK77ga3fPddD8+HDxzmH06CxhzgCQHHaqp5HVQ9N0EIcKeCmhFeqKUZOmyN/gvV/cHwWG7dsRr5SN4VYqU6fwF+8qyvMSF2UjAFgeRfzRh/TwxgJMc6OOW6Kiw9pMqJUAzhYdapFck2/8V1A2boavunolNYYd9x2xilTcIZHNuq5UGE5XPHZI7rUt9aAI1TQpY0gh1Fgu2pGp/OYuqw4c6MaeDyWWlyK7C6nbvp9x1AG207OqMYl1edMkMsWY9TwVxRItVkLQ2av5RUtjiBc4Svg8cpT2Bk1QmUosruRHy2yZ8TMypol5gG+YIPdyAesczGULmIyV8T+8ZzuZIhyCYJpYUKUS2jPHULoxNMN68rpY6HArqG0zgR6Yd/R49ztBydsDvzUIUOtkG0B4GTQ3BjgdNE7rLgzswuR2WMIHPoF93O3M6nVZRZmaULf+LN6qKXZ8e5Kb0OoktbDHydmy47xalNvv3alGhM3kmp5gMrW96i60MSOodg7mtOfpUjJhfnmwP5uDlZnuOUPNOTUeyZcVu99TskGM3yq5DzHo7vHcN/mk/jjG5biysVJ5w5P/i0rJPrb/wIsfN3ZH+AFhnBAxBfuWodVA3H8+S8V9Md24cpffRKkd7Wf9+fDx3kAXuHmZsA3aDgha3XZYsQqqnMkCOx3QmVXBo2CFVrtioUQLI4jWqmjGFsIwAglqisUASWHA+MEdTGkf6ZQoEKdJgMBQa2uYKB8hMmTA4gVWN2pmSJzAqt1aqlNpnCcSDun1oStakWtBBwyVryHM0XQsNZIc0psDsEDh8HuHNS2YylEXFp35PcBzJOxeUY9kxtRF6NspJZIU3eWqq6xpS2gVjGxHXsf9NjTyTZM5asQY2VdJCKXL6KrvA3T3VeAmoRpCK3rzAGhCghVIMlOMZZAbRYynGI5hyaceVd2EEpRrjbznBn3lMbmrupvx77xHHjifDwHrVST9WfDnNd0WF286E29CMWW0h+o5dWMSmMe27PurNjkbAU1MYJQE2fkVmhconW0ZfZDIGEUYwtRU2zvAJeQxOjMAYxS5x0cCoiAxxRHSuMglKIa4N+jbnemwlFblep5CEoFRC5BpoA9mNpSDNt2jbSyCo5wQwD1WhV9E8+iEkqiFlBzaCnVQxyJ+iyW6zJIoPVIJl6fwWqDnFUA7bmDQGeyYUSCz6CdxxhKF/GX/70L6xck8Ik3r3TusOU7wAv/Alz+PuCK95/18V2oMIpaX40/r38UJ5Ru1O67B5hxicn34cPHWQUhZIAQ8h+EkElCSJkQspcQckOj44rVOrdws4a6FNPlnh2fuXgkdiMgXajiwLix8jpVqKKmUAiEoE61YqjetaRkRUF8ehc6TSFQdpOKEBYuGCkymevDUwVsH+GopxFmCLXnjxlqdmrCvbZSPlOqWsQ2KBTnCD1y0OyoN5H/xPI+tPyURuF4/KyrrvQO6xbOmJSae16RyLOwqnlnrS7AcGLMfTR00Kxwhjxa0ZnZaWqbuopeUKpKmp/QmD0mK9IzuQmJGRaWVa7LCJcnEKhmkS3V9NC5UMVgPBMze1i9OA+YxXJC5SldXMMTVMb+ERfW0YQ2k6qkVjFQC8P1YtCoFHVtM1izMrosR9E6j5r8vxnxWfe8skpdbuIedcL8xPSc/BXackfQmXkFYr2AqiLY9mXti9njjnbs4Z8AIAgCuiadQjd2pFwEd9wguNxz0eIo+iaeQ7DqraYoqNdIE+jQWGqec11TnfhQJW25F4x3jWJi0anru9kdzsWWhjmrZvgO2oWJmqzgYz9khUG/+p4NCEq2S733IeAXnwCWvwW45QvnYIQ+rl/Rgx989GZ8JvbXKJXLSH/7TtAGlLcPHz7OLAghCQAvgNk/twJYBeBjAJy6+S1CqhdYjop775a/wuVJrpHOU04TCEGlJoMqioONch5vDklTxQxqtjAy9We0OAJQBanZGhTBWjgZAIKSgJosQxCM75hY4YRjP11BkFKPNCzjAy8HjSftXbaFTekpdUoNUp1fn0kzit1k1CM2Y5FQBUU7K8aRiddgVfBTMbqdlUtwQbEmY1qT7Pcw2nOc+mOeIhSwln5QKNUZTjsUSp2hcC7oTf0Glbqh/Ng1vaWp4xqNzwsECtcgd8J0P6mnI4mqg8a55ERld6hoV7lW791a3mroa582WC8IVqwqn5nO9ZyhnnpOHwAQ073WN/4catRq88VnjyJYySA8oRaMbzBmRVFcw1A1hMoen7uFz7rI+tvDYBm0a0WRa1+BSqgbgVoOcVW91Nawc1PJ6eyZ2zU7xYFqDvNGG+Wc2TvghaU3c19qO3u/p30H7TzFFx47gB1DM/j8neuwIGlbDTr2PPDAB4D5VwB3fQ8QnV+6Ps4OlnTH8K8fuxvf7v8bdMwewr6v34N6vXlJaR8+fMw5/heAMUrpeymlL1FKj1FKn6SUelMBHEQCTuVDbyPa+oXflj+GNo6zw4MosFV6ArnhymxdVvSeNIYjWhq17KOpPBKqqKvvhOv41WUF0eHfgOeL8EHxzIEUh72xNuBaH9YFozMli6gHBXO8elMvuoozNGItBGL9vDOzy5InlK/Uuc6o3r5rLqBhxEU598hkvoJcqYa9ozOYyle4LEXO5ih2Tm9noVNN4vh0gSuEAVgXAAStTp3H9XWTWm8VwUoaUr2ZEEelpXMFWHgvAYGgGsX5ssH6KQJzyLRzVSRrsOH8ThYCmBx+0qVtb+hlEPT9eRI5rTto5n4rNUVnCQkUHJmwLgJESmPomXxR9ykalQyocaT7zaiEkp5jdmudJ+vv2ob6HqOUohQZgCIEIChV7rXnPctSyelAEosyrjPHtxUQk6qp1zh4GMuWfAbtQsST+yZw73NH8XtXL8Qtl9hEP4a2MMXGziXAPT8GgrFzM0gfOuLhAP7sj/8ETy36M6zOPodf/eufssKVPnz4OBd4B4DNhJD7CSEpQsgOQshHCWmw3GlDdyyIADfGrfkvccBWpNYDkiAgVEkjVEk7agfZYe69LX8Mg8O/9Ow/UJtlohC2KZAEwsIrq7lGUZUmGLluZghKVS8HAPBD0LyQLlYdRmHP5IueBr9U1yIWnObkTKkKuW5lmOyha+YC3nZUago/Bw2wrLwLLp7tsak8csUKjk83V4rF7mCbEZKsTiAFdREwYagqxDL/guIdxsYLh0R2qQAAIABJREFUkTsVBGuN83cAxlI0U4PKCzOlGg5OsOtfC8TVdlWFQ9HqoMWC3nINc+GfnoqjYH6GynXZ4ihroah2ULA6c41Yv5GMt6Msi26ZlwxuDDjl5KC5QQ85BRN84TH4GgTanM0k1Qu68BATYWJ9VFtdEYJ2zazn2cwCA8BUQgt21t8G30E7z3BkMo+P/2gH1sxrx1/dutr64YkXgf98BxDtAn7/p0CUIxri45xAFAje/P7P4PDgO3Fb9r/wr1/5PCZy3uEqPnz4OCNYCuDDAI4CuBnAlwH8I4CP8HYmhHyQELKVELK1VCqbPzhjA6yEnO9uyWTo0wZf7ZRSmwHlZa2paooc41mwnaMbY2RG1/TLXMGEmK0uViv2kjYf5tpPzajZS7UCwsWx5nZuETOlqi4BboZZUIP97dIAIa2FS3mg1TuxTsWWGcyzCbeQ1EYQiHUuNCZTe160+VaEsLU/7SC3sD3OeLSrzK3hx7kgrTBLGprJxbQjX6nj4MSsZ64s0AS7rIrF5NuWtNS/26VrfI8K3GLSxniMZ40XucCHwlGzbQUUYjM1Gt2O9hm0Cwe5cg1/9P2tCEoCvvXeKxA236RHnwV+cCcQHwDe/yugY/65G6gPPgjBsvffi5nuy/Hx/Jfw//3r9z1XaH348HFGIADYRin9FKV0O6X03wF8BS4OGqX0W5TSKyilV0QizLBTiASCM+ejVYNOB82c79Toiz+nhndVg51N98natDlkphNsxZhohimZcVHD5DuBbNthk9FpD+GSOEyVqFTQld4GsQFDNJegRIBUM1gxNxNb0OqOzQGUYJvn5z1tVsZIJgLkOeh7Qae72Mbp4FQdV0Ks96wGQ9VPDXG0pX2IUNCTetH1Wtll483g1vDj5b81nG/OuFtU8QQMZ7LSIIRRaOC4aKHadam1KKxCle+IEi8GjLL/itHBpvrg5n5yEKqkm2beeCBU4ZZSaNZBFHwH7cKArFB8/Ec7cHK6iK//7mUYTJjo530PA/fdDSQWAe//pV/r7NUMKYTE++6HEO/F52ufw0e/8TCeP+SdqOvDh485xRiAvbZt+wAsbLYBWQyzwr6nOIBGjhPPAbOwWQ2++MeymnHVvAGtkADslqXFDiLEcxl8JrG26b680NVmF3AAtI69DGWvqzFXjlAzKFdrCJtrLVGKZT1WBypfqavKfnPEoAneBmMianVIKCUoVe0lB1rvt689zM2xO11ItdmGLDEPrveA+rxoYZOpsrVtoV7iqgvOJdzk8zWY89ZkIaT/LMSafi0B4NRBcxuP6qBZbEkT9LplgoSR+be2NAYevHJza1IUshjWQ1HdwFuE8UK0ONJ0CDkPbs/nqoF2JCK895Tt+GmO2IkJvoN2nuCLjx/AU/tT+D+3rcbrlnaxjZQCG78O3P/7QN9a4H2PAG2953agPhqjrQfB3/sxuoM1fEf8HP7s35/Gg9tHGh/nw4ePucALAOx1SVYAaEqtYzZ+EWrBREvOWa59hf77dNflfJU3E7gOmsk4aUnquVkQ4ggtM/9J4B2mVA53W/72yoHyAm91vJFqJdCAzTyLDtrxKWtOGQUQCTqdmLoYnTsGrcUkKYVSi/w9wHL8XPcnZ7ekriSfYs6byz1gf54mkEQp0q//LdbZNZv7QNgWYBp73eKotDYq2S3GMBBFtsNIi9HyLaOcexMwcr6adZT1OmQukOr8XMu61IaJ/jcyJ7rBwhOx/TzT0Aqi2yEQopfYmI1f5Hp8o0hd30E7D/DDl07i688cwXuuWoDfu3oR26jIwK8+CTz2KWDVbwN/8DAQ6/ZuyMerB/1rIbznPiwkE/ivti/jk/e/hH977ui5HpUPHxcCvgTgakLIpwkhywghdwH4UwBfa+bgYnQQlDRvKigkYFkFV4SQ6Xg3WL+628OShc06nVVhV1Dq6cg0DuecG7OJu0rO7dw9HNO559lz0PgV16xjK8QWqg7C3LgEXsziVPdVqPRdatlWl+UWc4s8ru1pxvly8450ZVGGdYMJ1+NTvW/Qf7fnTBp92ExhIiLddblePFwqTTUcZ6BF9qZVBtC8v6LOCcGp5+NZQZDtucIhwuEljqKHJDb5rkv1XYdq0P06uYIqniU3rINiY3AT3jmb0CuteQibNHq8fQftNY4n903g0z97BTeu7MHf3r6WfQnlJ5kYyEv3Atd8FLjr+0DwzMSC+ziDWHI9yDvvxcXVPbi/6zv43C/34LOP7G15NdSHDx/Ng1K6BUzJ8W4AuwH8PYC/BvD15logAAR3BT/H3lbjmZfr5RijzdCMBCRX43MuQWwWhU1g2tMJmgsHbTa+zCW/xLnNzup4juwMiIS4gfv6tgl2VUJJnSVa0nX6SsteuUp1KYa6rahxTVaQTax2OULdR/LOa2sFxeh8h9KkeXx2OELLPC6u2bFx341vCk/036gex46seYhytIVbK1dkdjw1RxCAhbmzwpRjKqj3Nm22HhyQjLqH3I3MvwX1UMLxXumIBCyLB5WQschvsLuqFH4DdguAhaFrFvbzK0XMKTrEch8KhEAhEsQ5fBfGQ1JDFc+BjrDHp+5jGc16C8H5DtprGNtOZvCR+7Zh7WAHvnbPZUzS+eRm4N7rgKGXgNu/Dtz894DgX+bXLNbeAfLWz+HSwvO4f/4D+M5vjuLj9+9omODrw4ePUwel9BeU0vWU0jCldAWl9CuUJ9XGBQElAsp1uSnygDkHVoGPjmgIyZjToNKcjoY5aLAbMu4ohfvQbROJ4I6TjcCyLd+2yPa5OxqzggzF6CC6OecOAJVQFyTO9xkFJ/TRrjBp+zhgasfLyJVCfEekGJnH3Z6LL3dtC3DKj1MKwJEjRnS57o4opzi4S/mGtpDEd+g8jGdKhOYZCpc2vViCZq56NdiBlUsWoa/daejyGDR76Gez5rjbLch7nuYlIvoB2nFe37uJiHMO3JxOAgpKBCzqYo5ZwfQc8e4fSSCWwVN98cFgtRs5SKGA8/Nc+0qM97/JaBeCTQ2WWiaXlwOmPddeCovGvqeSN2i9N80O7Mj8W5Dqv8HahxCYMwYtEhCxsr8dqwac4Zlmhjlsus5O5tl9LG5CSBp8y/01isOpPP7we1vQ1x7Gd993JWJBEdj0TeB7twBSGPjAE8CG3z3Xw/QxF7j6Q8Ab/gxXTv0MP7n4Ofx85yj+x/e2YLZ8OvKwPnz4OBOgBBDlEpZ0xVBpc1fLXd6rGf42g50IiAQltNtW5K0OF+er22QHtJITlOtYhU6OE+AERV3SDDTWmWzux6YR4nT6mjOaKqEudESCiIec50CJ6CoEYHdaHHlpavHhaEBEbzyMi3rbDIPRI3QzNn8Nd7ss8cUTqqGkbqxqBrpCApjsuQaF2AJH4gk19a+xPRQEsir1zmNG3ZjKi/vbIYkthtoRAQk7u6KOcWl3G1b2xbGaY6BqUEgAmeSlrp8T0lw4XzAQQHvYec0VIiHftsSSyyPYHOrTNcd5OYzmeW+Gne7iLHIoHrX8KBF1dkoRApBF1TnlODFLumPoiYdNx6qqk1B0x00W3FkcN+epEkrq97GsUIAIIGBh1hqs584pJ9CC06WozF9LoY62Z9Orv0pdBgVBxSWktxknsllUgx3c7dnEamDAyCHWHNjV/cYzxHPmefAdtNcgjkzm8Z5/2wRREPAf778K3WIR+Mn7gEc/CSx/C/DBZ4D+S87xKH3MKX7rM8D6e3Dl8Xvx8KUvYfPRNN597yak/FppPny8yiBgWUJEIhpEJc5XWIsFJbS387/gAQFj2bIjLC3ddRk0U9TMRmk5NprjMpNYi8neN1iER7xACbEYYV65RzOJ1ZjsuQZ1KYYl3TGUg93IdLLvGrsJ2+ZwsNgeZsfNbmxlOtehGJ2PWvfFmM+RaKeEeDogxajJIbYZ1TTE5lsQCBYmowgHBKSTl7FdPRw0QXQ6DXWpTZ/fRckoJvqut5yTprIXixnsWzWURDE6iBovxlETXCCCnsuU7mJOD885mOm/Wv9dc2rcGD29Cxdz7+a18zjXiqEtLCEeDnDHoDk1s+3LIItO56QSSgJLrsdM/+sxobIcq+cZRmo6uUGXTReUOiCIFsdTq21HBRHZxGrL+WmFs7MdF2O8/0ZPploRDefTTX6dJ2BhLASQhkz4+vkJoN05/7yISG1hhqrOkAYv54EQAtG0AGFegJlJrEG+bYmFhXOAw5CmkxtQNdVTrMmKeh0JCrH5qAXaISvWACx+KDA7i3zbYn2LWzilLMWQTl6KtItDz7tHq6Euy9/rFrgr3KZ63wAQglmX8HI6B2I2I4NvZXmb5nERFn49MvhW9ne7sxxAVH3GSuE+VHrXNdWX76C9xnBkMo/f+dYmUErxwz96HRbPbAK+fg2w/xHgps8A7/4vIHIKiZg+Xt0QBOD2rwKX3IVL9v8LHr1qJ45PF3DHN17E0cnmKtf78OHjLEAQMRBXDQHRPe+DCIaxQE2WGiWi5W8ezIaMZlwKhOCyhZ0otC1CPdCGeqANmc4GhoAaXmk2XM25R0oogb54GF1ayCERUA0lsSQZQlcshDpEFFWBE7vKvp4kTySkkxv0czLnh9gNslqgHSAEcs8qxGJtDseBkgBEgTjykrQWrWUD7CGOrC+rja6GsHmJhAhOo64U6QPUELW2sIR6II66ngtDdKdgQZeVJeUZ4ZRSkDqLhlDEEJb2tAGEgApBV+U7rX6SSIjuyFIhAPSvYz8dfcDVKA5Jzv21KWpGtjwgiXC658Ciy98GtPWiHu4GQNAeDiBiCgWTxQgCEeY0EyoDRNRDxdpCEnLtTEhVd8y49ctEyFLMM/dREcNQhBAUIrkavDUTozPddQUAmzNn8kt48xgQBa4TxAsd7YgE0RYWjTwyFeVwDzuGc7+BAtmSyekwLWx0tncgm1jtubBCoDiEaKSkc/GoFkxgat6NyLWvRK59OeqKAqsbyZ4T7V5f3tuG61f0AQBm25ejFGa/0wF3RrUUHYTMySssxBZBtpX9mI0vw3TXBv3vtpCEgXaDub7moi5cu6wbly5IYGVfHJQEABD0xZ1sYjIWRF2KIt+2xOLse+XmcfNFiYhKuMcR1qvdwwCAYBSVjqXcNtPdV6Dq8pkdvoP2GsKRyTzeozpnP3rfOizf+hngB3cA4Q7gA08C1/65n292PkMQgXd8E1jzTizb8Y/49TW7UarKeNc3N2LbyTNbo8WHDx/NISCJgMwMbpkYX+KTPdcg1XutEd7jsmLO2DHirfBlYZ5MoViS3dhobGBTIrgWVr1qcScWJKMISgJy7UZujCbjTyW1MLcQhC2VTv99pnMtStF5+oZw0MQEiFZDyuLALH+L5bN0cgPqgRjI4BWY7LkaPNTFqG58Le625svIUWYAC4QwtqatT2ciPRk0x5wauTgCCCIBCZcv6jTl4hCdGQyIztwy+3lSGDlwshhSGUK23yVL+KyYzmgZu7I+e1ag1s0XYihHBzA67y3ODwTBNTlL60f7Odnzesc+XfEI3rLGKWwxP+ktblKXYljaxxy0qARAriIoCVjSHcPirhiqoSRGBt+KSLfGDBGsnddhU2zkj3t03s0ADGXFsYE3YWzem0E4DmchttDC5Gq/aw4aBYFkYq9k0SWU0HQPac6S3Sm6qJs5Np2RIDKd61E3eQDZjtWY6LsBihh2OFvhoIhI0LygI7LFCwr0d6jsJXEuXNgRMJ2H2ald0h3DRWotPiUYV+8HAR1haz6XxqBpzkksJCFmCsXW9gxEjHHMJNZgJmENE+6KGYzr6Lw3Y6LvRswk1jjyVGuBNst7kr0ajX1642F0tYUgCQLi4QB79gD0xENYM6/dko+5uCsGShgbm+nagLGBm5BvW2yZEzs8czPN4wJpqWaht5iSAd+af41g72gO7753ExRK8dPbAlj207cBW77DVBo/+Cwwz33Fwsd5BFEC7vg3YPXtGNz8WTxx+UbEQyLu+bdNeHzP+LkenQ8fFzzCAQkYvAwIxVGihvFSl9pQC3aga2AxlnTHXH2nVpLtk7EgQAhInK1co2s5NizoxJWL1fAwEPTGGwmAMPVFbp5N/zog1o3S8ttQMIUwQQ0VEgLMWJ3ouw5y2KpEqBmnmlGnjVkyGcNVG0NkGYMUtJASWs6H1L0UihhGqvdaAGwVf6AjonWKSpiFHkVCAb3fkfm3IhSJGn10LASWXA/jIrCOAqKAKxZZz0PgMEwlNTRPM7QS0aCNDdQcKFtenHptLTlPFKCLr8VsfBkokUBA8KaLe3HrJQNoS/IdNK3wtDU7SJ3vSIerE8Fj1/iwGaZqR9WQKbxMPzeCoIsYBqDmoBEWJqjN18j8W6GIQQR6LsKqVZdgw+XXAIVJAMx4DwdEppxHRFy/oged0SBWzetAOCAiKDmdKfudq7FTgrZgrdbQqnGLNFOLY6C1aTbORQG6cI1CrHOoh+yaHLRsx8XIdqx2rJd3qm0EJQH1QJt+H7EEToJ6wAh/BFg43BWLkgiKAhZ3x0zhkYbrZ/EhGoi9rBs0wqrNz9q6+QmEJOtcxsIBdLWFLIzzwoXMcbTkkHFywkKmBZ9C22LruwPA+gUdKGtsmxBEPRBzV3AxgRDSUPAGhEAQ2MJJ3JbrZX63KmIICgkgGXMy1TrLz5nP11/kLFdV712Dy668tuH49fNocj/fQXsNYPPRabz73o2ICHU8vv45LHzwnYBcZbXNbv57IOAl8enjvIMYAO78LrD+HnS+9EU8evGvcHFfG/74By/j+xuPn+vR+fBxQePKpd0sH2XFzSjXjS94zQhc2deOcEC0GBrXLO3Bil6V8SECC3MEUA71cPvQDLiuWBCXLezE4Ia3AKveDvStxsKuKGJaaCABkrEQBhN8QQvWFvu5rJejVhjuAJbeCMnGIlUXXQ/MvwL9qmOkiGHUIl0Wo88cyGjZYmHZTM5aMAEx4lXMVmVzVIuxFuzAsp42dESCuKgnqu8jKKp4khjEuvkJDCTjeMvqfrSpDAQhYPLksObAJSIBrOhzzoEgWo08RTDmQjuVtpCE1y1l14qxcdq52vLg1L/Nq/ZjC2+FEE0i17FSNwgDksRYmy5rkVsKASODbzPmwmSoa3PZ3Tcf/VfdiQ0LEmwhAFbHbGT+rY5zNF+U3ngIshi2KCqaz0ITPtHnromyEDzcuLIXyXgUsYuuQTDsvD+vX9GD31rVp/++tNu4NgGd3fI2Ye2EWUV2Y0oFx++yym71xMMQBUF3Ls2sLyUCejgOGkCQWLgGw4O3ItX7Bod0flh1YMxFo9eanCftvMwKhpIgoiMSBAFhAiPqufHC8GTBuiijOSBm5sYuRa81ozmVWu6l+ZkWk4swNvBmPT+QmP4HgK5YAL3xEHrawpbtduVVCmC6awPG+99o2S7KFduZWMfYGQ2atjnvOe3Z5N0V9ucdAF63tBuxkIQNKxbr20KSiNXz2tmCCaedHs6Cl9y1AvE2+7vDONqu5tlsFQDfQXuV4/E94/j9776EK2MTeLLj75B8+SvA+nuAD70ILLnuXA/Px7mCKAG3fw143YcQ2fYt/Hf/f+ItK5P4m4f24HO/3OfXSvPh4xxAEgREQ4YBr8lyBwTBZtBa0RMPIRoyvsSX93Ugv+x2ZJLrHftGgxLMxsmCZJQZXmYnSn/8mQE/0BHBusGESTnSDOt4eJL7Acm6jxBpBzoX45LBDixIRvU+LTlLmo+iG65Oq4Sozk8pMoDkurfqDINmt+a6zefvPN6uPkiJYDho4QSCkoT5q16PSFBEIsoMzq5YCKBaCQSjzXmJCCIBZ/4PkWzbzKvqpiGJoogNCxIgVDYxZMYOnaaxSqJoOOSWM7QzVwRYdZvOFrKQRgGBgITBRAQr+ow2zKzcoq4YREHQQ8kKJvGUkCRwa5itG0xg9UA75MHXYar7KsRNiormmV90+VuxbsPVkCSt5IP1uuTbFltUADUj3n71OuxKdn1rLX8GJcGag2h6bno151H3g71DNDXILt+L1hxQYhlfe8Tk2MNaUmDD/ISxGGK6dkQQcPmiTiiUohZMoBq0ClsMdISxaqBdl9kHoIcYqg0AACIScWxjYxT1czOLCWn3j1nAYnTezboYixl251W7rfW51HM22d/TXZez8xeDOhMl2BitkChgYTIGgRAsfMO7MTrvzeiJh7DctvDBHj3RkXOmhU7zcN3yHlwy2MH3bpZcD8y/Ul8s0BZxtD1rUhuIKfRYQ1hdtAlL5nNgObm5jpXINxDeMc7H3eO6uL+djRtG6K3X/mb4DtqrFJRSfH/jcXz4B1vwqY4n8J3KXyBYGAN+5z7gHV8Dwl4rjT4uCAgC8NbPAW/8NKTd9+Ob9LP44BUJ3PvcUfzpj7aj7CI168OHjzMDe/0dzSC8eCAO/evWxVEzH9kTDwGEQBFDaqL8FUYfxL63E1p4FgXRDcigJHALrhKvvGViNXQ0aPk5gkD0cgD2XB0Hg8Zpy1BIpJjfGbUFHALlNiZkkIgEMJCI4NIFjQSwiB7eJ7b3AmvvABILAACxIAtfbI8EGINGiNW5cJlS0ZGDZjaIzV0LjGmh1HSNie5ErZ7Xrq/wV9oX6nYmpZy5MrcshVgujopIQMRFalhnOCCafHH+CUz03QAxaVb4I0j132Apjgyw+yMalFCLD0IRQxYjkhAYTka8F8HBdVisOuaUSJa+s4k1GJt3k7k7+0zx0Xsx0HOx++emPgY6IogGpYbhwPb0ogAnB81eh1D7fV4igptW9ekiEpWOpSwHjxBM9lyDmcRaQ1E01A70GnlW9pKJV1/UgzUmBUsCihV9cZ1Zssv8a+G8a5ctNjZqYa1EVYAkBAQUPCV/RVXVZGwbYcIY868DEqa6hep8Xr6IXVftnaEzayaxElkIoRzpByHAJYMdCAaDuGJRUg85NJxt41lXhCCoEIRAiO78LUxGsWZeO+LhgO602NHfHsZK9Zkxz0syFlTfO8TxGdp6gU52boFazrI8Mp28DOWIGk5pXxzT7h/FEGAhghHune68VA2F5kNZcA3SyUtd1UF1dC8HFr1eD71tthTG6WtO+phzVOsK/s/P9+D5LS/jFx3fwcrCLmDlrcBtXwba+CEvPi5QEALc8L+AzsUgD30En+r4GJbc8EV86tkxjM6U8M3fvxy9HEUjHz58zD14RZQBzeixhb1Z1NqIhQVgtaMYch0r9e0ziTVoL+/3LAwMGMd22BXKdBYgqK9WhwMSE2ej7iFj9rAee3iUPmgV0aCk/2mX5iaEiSUcmcrrDBooM7cMp8V6TDIWwrJFSSDgEqppKtZbiC1CLRDHpckFtn3MzJeWC9Z4jVq0yeybWS7LNHQvB/ITWLZoPkb3nlR3ENAeDuCKRWEIbSF0t7dhhLwVXdEQyOyYOgZrO3YhBAC4YlESYyMAFUJMkKOcMz5UDXS3+lDXrFqEaCiAx/QcZTb+VN+1TN5eHacGLfzSnOtFlt2EKTmnnr/WjCoYIUXMW08P/WuByf1N7cpsYnWM8zYglz4JWYpAFo17pC1kPCdXLE6iS7EubNcCcTX3z5nXFhAFdS7UxQ4xrOfgVUNJJlHf3wuM7QCWvxmoGyVv7MITsVAA4LCzvBwnUSCohHswPfBGhOYvB3LHmeiQRfXVCHE0M2hT3VciVjhpq9FFAEIgR7qA/sXAzu0A3Bk0zdlQgu1A/GJgcj+6YgFod8/SnjYsTS4H9u1jbYsBLEhGkR3JWvrUxmVmMcMBEctU5nhpTxsWJqNIF6vYeGRa36e/Pawv9NiVLlnTje81gwVk4jjBLLt3NYe+KxZCV1sQYnscmNgFRI28MkHNx+2KhXBRbwyQqmpTBPbSJ+VIP0q0ynXQgqoTJkkiMMBKkVzUk8WRyTwkgSDVey2kesHzPHwH7VWG6XwFH/rBy1g09DM8FfkBAooI3P514NJ7mg9c9XHhYd3dQMcCkPt/F+/Z+QdY8cbP4fd+I+IdX30B33rvFZb4dh8+fJwhuLyiBYEAChh7Q9Q8C9VYcIR6wb0wbik2iHT/UtBM2nMYmoNjb4bEegDMYKZjNZKZHQCYghtS7PPR+W+DMwXeaXCaDRKtQHRQJIDMBAdEYpYF18ZiHBNXw8aW9LZjZBom50xdHedqVHDmJNgGVPNArQQAkMUoQAiqoS4Lm8c6HQDIDqB9PjBPle4mPMaPOW4ECmQxAtHhdLuEj8f7gUvehYsAjO6zOuPadHVEA5jMixBEg59SKDXNDeWGP/V2RLG38xLUVCl284XVCJSYSy2zZJuxQMdyYVSHQwhA1hz99nlA1zKg52IsVgt6L0pGgQm1u2gnqFCytFvr34BcLogOl4K9GhiLw347PTiP1x2rrosw22E+T42ZMq7VYCIC2NRKU2r9upBqTM/vjGLC7rRrN6MgAPaglO5l7J86PlEgkBWK65azp+ji/nYcnJh1sOXGKWlMK/vx1rX9qMsUT+yb0AVD0LkEmDrIcs9N563fMabbsR6II5tYA6I63l4mo53tV2zvDIGALTpM7tcLbuvvJTEArLodoDIgBkDA3mmVxEVAZRcQSUDJK44x2McjiQIC9udL3SfbsRqVMIeQMCuY2mBXoxXUla5FSTVXVmWw2yMSVmnF11ffbpnEpBpmfa16DUHDQMd8XLrASVVqERI8B21RTwLxYgzdHYaSpPn8a8EO1Bo8O76D9irC1uNp/PV9z+J/lr+GNwe2AAuvA97xdSDBL3bqw4cFi64B/ugp4P7fx+UbP4znLvsQ7tj3Jtz1zY34wl3rceu6gXM9Qh8+LjiUIgMQSAVvvLiX1XnKqaumgojLFnaqEWDWL3iBuAuyMQPe29g1AuXMVWYFiEuvRyy4Bunh4wCANfM60NXXrjtovN54MBskg50REAIMVmeAScNhq6mCDFoOWsLkiEoCCzekiTaMqCMmICYGzXsYN63qY+co9bLwpFoJciag10G7ZmkXHAhGgbV3WjbJLnXqJvpvhKBUUAuyS1wHAAAgAElEQVQmcLHN0TNL8tcWXgvEnQW13QauGbgicctCIbafxl/F2EKTvL4xJi3vry/qfU/cvKYfokDw5L4JTrdEV4ImgC4uYnxMHL/TYAyz7cvRoR4fkkTIvHg7zvmcEgQ7kwnXEhGJaBC59pWIDSwAmigT2hY27oMrlnYhr/CUTxufw6XzWQguUcN+V/bHsbI/Dsyc5B8wsA5LKwqW9DGGhTnQNi9Qk2+3MWgaW88Ll+vvjGO9kMDu0azruAW3Z00FIUTvMx9mtkPYPNeiBM2F0JqoR/uAFe8CAChKUe/HzjxZTs/0O8udY+ebjy9xGZiIxV0xlGvOe+36FT2QSwZLKhCCt6+fBzIyBmTALagOMaCXRQGsuaKsPwIsvBpidthxqJeDJvSvQXcwYrHfNeevI9qcmqrvoL0KoCgU33zuCF769U/wg8C96JQKwE1/B1z9Eb+umY/W0LkY+MNfA49+Ej0vfwNPDm7Hn1b+BB+5bxu2n1yCT77tYs+6Hz58+DgdOL+o08kNwJoBtKs5JGbjmq96qDlhDAMdEUgiwVCaGTx2cQseOqNB9MRDuDjerrMgEERAELFqYS8yk8zYkATVPIokoBAK1PntAYzpy5aYIWM2SESBMKGQlPW9Egmy813W24aB5QPYcpzD+mlzQqml0LVm0OlMoHHiAGxskRgAAhFcfPmNOLabhQ02+46jQlBny8xzLksRyGCr7kGPtgIdAwCHATXCWQX9/MynIIlEj84zG8iZzvWgXVkgZuUxnSIY1rCxtfM6EGr3PmfNuG4LBVCpV7CkO6YbjK6QQkDdrqxnB8vhWqvmWJ2w2c26T6n+HBu4CZ5Y9XZwWUpRAla8FSikgJFtrGciYMNCqwDHDSt6UK0r2JhbhqWJBELlHCpceX3myM0UrcIUfe1R9HFDaRs4aIRwrlODY6UQksteZ9vTtm9AXQAIqnXKKAWFgJ54CELHAPp74zgwPguA5ZO9fCIDgbBnoDMSwMkmx6SXFTCHOgoisOo2kJECkCkhGmxcAkSDJjLT3RZCsSrzz82G6a7LQfCSd8NSiCtkBKj3uI1JJoToDHsg5LaY0toCwhuWdSNTqGI0WwaqLgXdBZExkCYMdERw85p+hAMibl7Tbwnt5MF30M4xUrNlfOrHW3Htsa/ge4HHIHevhPCu7wD9l5zrofl4rSIQZvmKC69B8BefwDfwUTy44k/x57+h2DE0g6/ecxn6O/y8NB8+zjSuW96DfLluOCIALDRR93Ig1gN7DhpbFWeWUiwkYs28DoiE4Ph0QWUO+KGAGkSBsHo9s6baiIqxMq8rtmmGybKbUJutAEemXM9l7WAHXjjMPueHYFq3tYcDuHR+AtK8AUAUIBKCTOc6VHqiQP4gO0JdoSe2MEhHiGMTTmlQEpCMBZEuVD1rfNtRC7YjWJ0xNszbgNu7BvHQDsbt8RiKFX1xdLeFuOGpgFP0QYNR+NkIUTPX25KlCOjAEtfYNH2z7fNwQGQMYRO4akkSM8WqoYToheVvcTho3JF5OCeW8FRV+MYTnMLgOkJtQDAGjGxTnwM+ewYAN67oRUc0gP6OMAoVdeUhsdCdzXJhL42PmQO8oi/OwhZdj+cgbAtl86hX5pjG7hVAOMGc5dRefafg6lswGIw6k8lMWNgVw0xnDCemjVynsYHfAqEy7PE0Nv/MaFYKYd2CIJb2xK0MWgMkokHdGdk3lmt8AFjYbcMizi6st46VbwOGt7DF6qjKpKv5gYv7ktjJ84nMfbYPArkRzy6625iTuCAZxeRspaV50fYNB8SGC0m+g3aOQCnFw7vG8J8P/gJ/p3wZK6Uh0Ks+CPHNf+ueCO3DRytY/zvAwqtBHvww3nniH3D14jfhPaN34davFPCFu9fjjSt7z/UIffg4vyBYv6iTsaCTpdCMSrkKLFRXz22hYbGQpBua2mrx+gUJrJvfgZeOeeefWfsyGQABw4DXixo3Wjh22aGhahkASGFIK9/IDGowR6cYW4BqolN30PR8KF2227y1dWgOkOJhAJsRkkRM9rwehNaxFpvZRrX2GCEElFLdiFJIAAOX3YJdw1m8Lu6+iq8ezJ0jbYsoEE5umzu0pjR1O0dO09IbgYi1wDaW3QSUMo62gpLQnHMGMKdA4p9nKynxulpmYjHgvgbQHAgBpDCAHADBNXxOCyMLB0TDgF5wFdC/DmtrD4EQYH8kgJliFQGRGE61W76YulkSCIKigD77IqfXhITbmZDIoV83d44whQUSAsT7gAqL1YyHJEyAQAg7yzRYIIUh1MsIB6z5eIpbEXPtp11uH+x+bSYszz4FdseFN0UJl0UOz04EEUgu5X8ejLHnwQwpDCALKkUA8Bhh08AWXdP0UMIB0SgzAlbypMlXDwBP3xqA76CdE0znK/ibB3ehf9/3cF/gRyDRTuCOB0CWN6D+ffhoFZ2LgT94BNj8DQw8+bd4KrQZ3xL/f/buO76t6nz8+OdInvGKEyfOXmQPCAkBAkkTZtkzLRTaEqBsWvhBW6ClQPultJQywiqjzLBHyspghIRAEgLZO850vPdeWuf3x72yJVmy5Ckrft6vl+JYurr3nCtZOs895zzncn7zSh2/OHEkfzpngrmukhCi3aITgm8Ta07+t9e2uFlaYiznTBnodZW1qdEUYuvY82qzR7pop7ucCc0v0oQyIMrvkJ5eZoAwbKYRGPQZ2RicgUfw5BmLmr0zTmuMOcTR3YPmp5UTSvY282eojSR3xkStorEoi9f5mjO2H6U1xvC3gvQ5uCwxHD8wncHp/ZslWPA1ZWASCfUpzQL2pgQMyv85DFhOxYVTPdey8nlugp/ULvG9jVsH830ZjHMduC5GKnYr1SPPgsHpUJzbtLhzmwthAeW9fllruAOHKYNTGN63F9lldTSmQAkQoMXHxEG98dyzp/ibzx2kMHEpRiIZz17t1uzFfC+NSU9ixFHpLR8LYPRpRrbPAIkCfed7Ni3NEXheVVu19PdosShOn5DOV41zI0M47qSLW1eAoSdAXSk0BAjQOigB3zSf4bbBBOstlJZZF9Ja8/6GbP67+Dvudz7NydHbcY09G8uFT/v/gBWiI1gsMPMWGHcOlqV/5Ma9L3Fx6ipu/OGXnLevhMcumxrC+kJCiKBC+aKPTYaUod7zEwI8z98QGOWRsj9oHOLu/bDGeA2Bc8SkkDfwNMb0CZaAymOOnJ9EEV4S+8P484wh1inNF8Z1JzVweEZoZlBX22uwd5IQvH/6liWQtKRYiqobGnsNWiNmincCkZT46MYhjA6PdciCBWcAqb2iwGGBWLOXw0wsYuZNISrKEjBTZ0htRc+NBhwdwhPaz6KUkXHSfB2MhBbmwukhFDomzsiwee6UgQHrHrKENBJii9HK2liOtrBYFL17Getr7YruRWova8C6DElLJrpvauDpAdYQmtNDZkD+NuPCaQDuwGjiQJ+1bj0Wh471WTx9+vBUYqIs2Dzn2kXHG7eaEIcXmlFU34RYSmtsDOqEaRCBXnWvOaXjzwNc/FQZn11Ny0O0Q1QMJA0gyrwo1izjqVJMHJhMgHXMO430oHUT+wqr+NP/ttM3cykfxr5EQowTznocy/SrOyx6F6JFfUbCFe/Brk9JX3Y3i2Ie4NPaU7nx2Us4+6RjufPMcSQGSNUshOggSjUNbWwDq4WmddCCzcdwz/fx05PissYFbCA0DqVrrejAjbox6YnUO5zGkCB3mys+lZwh5zbbtnmafRXS9+SY/okM6h3f6s+xKYNTWkzIdebEAd6N32AGHQuJ6V4L4EJT1jfPAGVAqMMNPbmHyfafCP3Gtv75bWC1KFxO3fgy9EuK5fiRfUgPss6mO5une121ZssftMXg6QzqO5pElRRwHmBAft5HSXHRHH/qxVBb0qzXs/Fp1hgGJITwWkW3MBcwKhaGHBf4cfz1lpr8rQlmGpJqHDO7rHmvvN+ea5rPI03tFUN2WR2DescxcZBPcNhOaUkx7C0keFIaQEXHglJ0xiz5Qb3jibZaSE9u3oMbjpFEwS72SGusk1XU2nny670sWruTB6IXcmHMSvTAY1GX/Ndj/QwhuohSMPECOOoU1Mp/cv665zkrfjXPrzuLC7fN464LZxgLoQohuo7ZWKpOHBF0U6vFAkpR0H82Q4b7WSfIk8VizEWK8R566W+eiackM024Z2O2vZcR46KtzBjRp9n9p01IJ7uslpgoS8CFqgkhSQgY9WlNcObe48CUlud9x8dYG7NShiQ63pjLlrfV6273MDJ343j6sFSUz5IAwTLdGTuwwJR5oZenA1gtCrvTO3gOdt4AHGZQ2my9q/awWFG9+uCZemP68NSm921bRMdDypDAj1tD2PfEizrvgrvn+WvFMRoXnvb5m5owMAmFsUwGGAtH90+O65SLtP2T4jjv6EEdOmyyLawW1XKCtKiuTZ4W7GxIgNZJ7E4Xb3yfyYLlexldv52vEl6gj6MAZv0eNffu0P7YhegssUnw07+jZlxLzPL/47c7FvEr+woee+si3h51GXefe7SxfosQomtMvpSKLbkkB2lkWs3GmSMmGR0Twpy3EOchtbRWEXRwu3Po8VBfAUBibBTjBxhX7EelJVJcbWuceO8OZDq7WRes7m0W7z0nxXfdJM8AeVRaIgeKq8PeiA3EPWfOGKIaOFidO7Z/Y28ZGMsIAVj9ZMPsSO5epOCaMkqGZNCxUJ7Z7CKHX6EMc+wQoZ9L99+Q02f8XmyUlWN8pja0NTgbkhpPXnk9R/VLDLhNqO9rfxeNYqM6MLgPZMSs5tk2O5nMQetidqeL/23M4akVe8krreKRfp9zkX4blTAELl7SqgwxQnS6PqPgZ6/ASbeS/MV9/C3zNXKylvDsUxdgnXYlv/vp5JazlQkhOoZSnDYhPWhjJNZjflVLa3SFdMhWbBFSz06oevuf+xYfY2XO2KZeQfe5cLh0ZE4F6D0UstY1/uo0ezGsfuoyZUgK4wYkddsAbcrgFDZnlQceCtZvPCQPapbtzx0YtCYpStcIsTx9j2rM7Bl2scnQUBm0p8fz7eV+rzlbk16wtcWKsjJrTOfkUTjpqLTGNdU6VVKQkUMDj6GjLxXJHLQuYne6+N+mHJ7+eh+HS2u5ND2fv6Y/T2LFHjjmF3D2v4xUq0J0R4OnY5n/GexbTvrX/+DveS+Rt/V//GfLRcSfOJ9r50wgNYTx40KItgvlCvZR/RJxODVJcVH07cqLJ2FoX/dNiCEncQQW1d7c7P4FWnets8RFuddA8h9Yx3RFT0Eb9U+Oa3n4+4DJfu9uDEq7W4AWKJ1+dzb2zFY/xT0y0tXVGTA6SL+kbnKB2GfR6Y4QLFmOBGjtVG938tGmHJ5duZ/DpbUcPziGN4/+nCEZr6OSBsBlb8KE88JdTCGCUwrGnE7U6NPgwAp6f/UQf8l7mYJ1i3j1+7OIPv4arjjl2JAm+gohOofVoto9iT9oU01ZjMyDPmshdbXR/RNJ6fUTUhJiIrMHzcf4AUmk9IoOfR2yI4Cru/agHQHvJ1/u3s2U+KbvaPffrbsn86zJA5olDBHhIQFaJ8mvqGfh94d4+4csSmtsTBmcwkdnVHPM1r+hMrLhuGvh9Pu7fEyrEO2mFBx1KvGjToGDq0j8+hH+X/Y71P24iE9+mE3RxKu58MzTvBZoFEJEjhZHRirgqFPAVuPViA1HA1spRf8gWQLbIyHGSq3N0f607yGyWBSDewdPrHEksZlZHENZnqBLaHd00k3K04H6JMQwd1x/kj2GBLpTyrtHwLRnWYLOdNJRaeSW1wXf8AgS7GNHArRW0Fqz8XAZr67JZOm2PJxac8aEdG6eaOOYXf9Gfbsc0sbBNZ/DsBPDXVwh2kcpGDWHhFFzoGAntpVPcsnuD4nevZw1OyexYuB5jJ97BTPGDw862VUI0X0cP7IvWaW1XusBJZhX39OT4yA+sVmCi27XA9IBjhvRh+LqhtZlaBStMrxvApklNcRHd5Nz7F6aIn1SeMvRSXyXHUiOi+a0CekkdPP3eL+k2O4znLGLBEvEJgFaCPIr6lm0KZsPNmRzoKiGpLgorj55BFdPjmLQlqdh8UIjK96Zf4fjr2taHFSII0X6RFIuew5qHqRq9YtM2LCQkwoepu6dx1kRfQLOyT/j+NMuJSUpcBYnIUT3kBgbxQSfhXATYqM4e/LAgPOgut0cog4QE2VhUA/r0epqUwanMGFgkt9F18MiDEsUhJusb9o9BfubkFctgOLqBpZtz2fJtjy+P1CCS8OMEalcP3sUFwyz0euHBfDa28bGx98Ac/4IvZqv8SLEESUhjaQz74Ez7qbh0PfkfPMax2UuJnnzt9Rs+gM7kqcTN+EsRhx3NtZ+Y47Icf5CHKlaSlIhveSiLawWhTXA4s9CiMAkQDNprdlTUMU3e4pYsaeQHw6W4tIwKi2BW08ZzSXHDmZEzWZY92dYuthY1X36fJh1e8uLGwpxJFKK2JEzGT1yJjjtHPrhM/LWf8zQ4u8Y8sMa+OE+aq3J2AZOJ3nEdCz9xkDfMUa64hDXZRJCdC9DUnvRv4cNQxJCiHDo0QFaQWU9PxwsZVVGEav2FlFQ2QDA2PREbp47mnOPHsj4pHrU9kXwwUIo2G6Myz/pVjjhJkgeGOYaCNENWKMZMfNiRsy8mHqbg2/WryNz03LiCzZyzOEMErO/wYJH2qheaZA8yFh3JDHd+2fSQOP/iekQJdkihehOpg9PDb6REEKIdusxAVpFnZ3deZXsyqtkS3YF6zNLySo1MsYkx0Uxe0w/5oztx+yxaQyMroOMz2HFR7DvK3A5jEXqLngKpvwMomXMuhD+xMVEMeekk+Gkk6mst7Mqo4jndmSzb892+tuyOcqSy7HOUkbXV9G/PpuE3M1Ya4s9Mmt5iO9jBGxJ6ZA4oOln8kBIHmL0XCf0a1roRQghhBDiCHBEBWh1NifF1Q1kldZy2LxlFFSzK6+SHI/0nWmJsRw3PJWrZo7guBF9mDwwiaiKQ7DnY1i0BA6vNRqMSYNg5i1w9OWQPjF8FRMiAiXHRXPe0YM47+hB2J3HsTmrnNX7inl5fwmbDpdhdxrrsgxJjuakgTAjzca4hBqGxlTR21GMqi6AqgKozoeiPVBdYFws8WSNMXrj3AFbymDjp+fvstSFEEIIISJIxAVom7PKWfBVBvV2Fw0OJ/V2F5X1dkprbNTanF7bWi2KEX17MW14KleeOIwJA5OZODCZ/onRqJJ9kL0W1n8HB1dBZbbxpP6TYPadMO5sGHisXJ0XogNEWy3MGNGHGSP6cPvpxgLvO3Ir2ZJVzpbsctZllfPeHjuQCCSSEDOE0f0TGd0/iTFjExnTP5HhfeIZEltHXF0+VORAZQ5UZDX9P3M1VOaC9v4cICYpcPCWMsTopYuKk4Qmwi+l1D3AQ8AzWutbw10eEWEGTzPmrPsaOFUSiwkhAoq4AM3pclFaYyM2ykpCbBR9EiyMi0uiT0IMfRJi6JcYy5DUeIb26cXAlDiiHDVQsh9KNkPmFli7CXI3g63K2GF8Hxgxy0j2MeYMSB0R1voJ0RPERVuZPjzVa05Lea2NjIJq9hZWsbegmn2F1Xy3r4gPN2Z7PTc9OZahqb0Z1mcQQ/rMYeiIeNKT4+iXFEtaryj66FKsVblNwVtFdlMwl7sZaoubF8gSBTGJxnIZMYkQm2j8tESZN6txU+6ffi7cnPkgJPbv6FMlwkgpdSJwPbA13GUREarPKP/3p43u2nIIISJKxAVo04el8vENx4Gt2rg1VENDFVQfMoZAVeRBdr7RKCvZB1V5TU+2RMOAyXD0z42rWoOmQb/x0ksmRDfQu1cMx4/sw/Ejva8qV9TZ2VdYzeHSGrJK6zhcWktWaS3fHyghb3MOWnvvx6KgT0IMaYn9SEscQlLcySTERpEwwErC8CiSoxz0dhSR1FBAsi2fBFsJMc4aYpw1RDtqiXbUEFVfQ1R1KRbtQGmneXM1/R+N12E1LO9zgNr4evPXpkd9y+fzK1alsFrAarFgtYBFKaLM//veZ7Hg/ZhSLd7X+JhSWK3K+zElqdNbopRKAd4ErgHuD3NxhBBC9CBdH6DtWQrL7jZbLdporWiX+X/d/KfnY9oJtprm81A8WaKNbHDJg+CoU4203n1HN91kEWkhIkpKfHSz3ja3BoeTvPJ6CqsaKK42b1UNFFU3UFRlo6SmgYLKemoaHNTYnNQ0OHC43CFSknkb0zEFXVYClHTMvrqI1dI8aIuyWrAoxV/Om8CFUweHu4jh9ALwgdZ6hVJKAjQhhBBdRmnfy7stbaxUEVAD+BkjJNohDTmnHU3OaceTc9rxesI5Ha617hfuQrSGUuo64EbgRK21XSm1Etjubw6aUup6jGGQAJOB7V1W0K5xJL5HpU6RQeoUGaRObRfw+7FVARqAUmq91vq4DimWAOScdgY5px1PzmnHk3Pa/SilxgHfAbO01nvM+1YSIEDzee4R93pKnSKD1CkySJ0iQ3eoU8TNQRNCCCE60UyMq6c7POboWYGfKKVuBBK01g3hKpwQQogjnwRoQgghRJOPgPU+970C7MVIt2/r8hIJIYToUdoSoL3Q4aUQck47npzTjifntOPJOe1mtNblQLnnfUqpGqBUax1sftmR+HpKnSKD1CkySJ0iQ9jr1Oo5aEIIIURPEuocNCGEEKIjSIAmhBBCCCGEEN2ErNAshBBCCCGEEN2EBGhCCCGEEEII0U20OkBTSt2jlNJKqac7o0A9gVLqAfMcet7yw12uSKeUGqiUek0pVaSUqldK7VRKzQl3uSKVUuqQn/epVkotDnfZIpVSyqqU+j+l1EHzPXpQKfWgUkoy6kYwpdTNHq/pBqXU7HCXKRDzO/xHpVSl+Vn5qVJqss82yvyeylVK1SmlViqlJvlsk6qUWqiUqjBvC5VSvbu2Ns35a6NEan2CfadFWr1C+fzr7nVSSv1EKfWJUirHfJ/N93m8Q8qvlJqilPrG3EeOUuo+pZrW/eiqOimlopVSDyultiqlapRSeUqpt5RSw3z2EauUekopVWxu94lSaojPNsPMz5sac7snlVIxXV0nP9s+b27z++5Up1YFaEqpE4Hrga0dcfAebg8w0OM2JbzFiWzmh9tqQAHnAhOA3wKF4SxXhJuB93t0GqCB98JZqAh3F3AL8DtgPHCb+fs94SyUaDul1GXAAowU/McCa4Clvg2YbmQu8CxwEnAq4AC+Ukr18djmj8CdGJ+hMzA+R79USiV5bPMWxmfCWeZtGrCwswvfkhbaKBFXnxC/0yKtXqF8/nX3OiUC2zHKXufn8XaXXymVDHwJFJj7uA34A3BHB9fFraU69TLL93fz54XAUGCZ8r6w+ARwKfALYDaQDHymlLKCEZwDi4Ek8/FfAPOARzunSkFfJ8xyzQOOB3L9PBzeOmmtQ7oBKcB+4BRgJfB0qM+VW7Nz+QBGRrCwl+VIuWE0jlaHuxxH8g34M0b68fhwlyVSb8BnwGs+970GfBbussmtza/pOuBFn/v2Av8Id9lCLH8i4ATON39XQB7wZ49t4oEq4Abz9wkYF2tO9thmlnnfuDDVw28bJYLr0+J3WiTWK9jnX6TVCagG5nf0awLcBFR6ftcC9wI5mMn9uqpOAbaZaJZ3ivl7Csb6kFd6bDMUcAE/NX8/2/x9qMc2vwTqgeRw1AkYbp7TCcAh4Pcej4W9Tq3pQXsB+EBrvaIVzxGBjTK7wA8qpd5RSo0Kd4Ei3EXAOqXUu0qpQqXUZqXUrZ01JKCnMc/jtcAbWuuAV6NEUN8BpyilxgMopSZi9GIsCWupRJuYQ1mmA1/4PPQFRg9VJEjCGE1TZv4+EhiAR53Mv/lVNNVpJkajZ43HflYDNYSv3oHaKJFan2DfaZFYr2Cff5FYJ08dVf6ZwLc+37WfA4OAEZ1R8FZKNn+6PzOmA9F41zsL2IV3nXaZ97t9DsSaz+9SZu/f28CDWutdfjYJe51CCtCUUtcBozEieNF+64D5GF3b12H8Qa9RSvUNZ6Ei3CjgZuAA8FOMIUf/xBg+IdrvDIwvnxfDXZAI9zDGUJadSik7sAPjivKz4S2WaKM0wIoxFMlTAcbneiRYAGwG1pq/u8vdUp0GAEXavGQMYP6/kDDUO0gbJeLqYwr2nRaJ9Qr2+ReJdfLUUeUfEGAfnscIC/Oi1KPAp1rrbPPuARi98MU+m/vW27dOxebzwlGnvwLFWuv/BHg87HUKOjFdKTUOo6t9ltba3t4DCtBaL/X8XSn1PcaH8FXAY2EpVOSzAOu11u6x7JuUUmMwvswkoU37XQf8qLXeEu6CRLjLgF8DV2A0TqYCC5RSB7XWL4W1ZKLHUUo9hjG8apbW2hnu8rTFEdxGORK/0+TzL4KZvU5vAL2BC8JcnDZTSs3F6CSZGt6StCyUHrSZGFcJdyilHEopBzAHuNn8PbZTS9gDaK2rMT6sxoS7LBEsD9jpc98uoLtO1I8YSqn+GBODpfes/R4B/q21fkdrvU1rvRDjoowkCYlM7qul6T73pwPdOjOvUupxjEntp2qtD3g85C53S3XKB/p5DiE3/9+frq93i20UoMTcLlLq4xbsOy3SXicI/vkXiXXy1FHlzw+wD89jdCmPIYFHA6dprUs8Hs7HGEmQ5vM033r71sk9AqGr6zQXI/FZnsdnxnDgYaWUu1cw7HUKJUD7CCPD4FSP23rgHfP/tvYWoqdTSsVhZDTKC3dZIthqYJzPfWOBzDCU5UgzH2jA+HAW7dMLo0HvyYmsSRmRtNY2YAPGEGBPZ+A9x6RbUUotoCk42+3z8EGMxsUZHtvHYWQpc9dpLUZykZkez5sJJND19Q7WRskgsurjFuw7LdJeJwj++ReJdfLUUeVfC8w2n+t2BkamwUOdUfCWKKWigXcxgrNTtNa+wccGwI53vYdgJN/wrNMEnzT1Z2C0LTZ0UtEDeRajLp6fGfdhCuYAACAASURBVLnA48Bp5jbhr1MbM6KsRLI4tvkG/BvjCt9I4ASMzEaVwPBwly1SbxipaO0YmQZHAz8DKoBbwl22SL5hZKXKwCdLndzafD5fBbIx0maPAC4GioBHw102ubX5Nb0M40Llb8wv7wUYSQCGh7tsAcr7jPl9cyrGPAn3LdFjm7vMz89LgMkYwU4ukOSxzVJgG0bjcqb5/0/DXT+zbF5tlEisTyjfaZFWr1A+/7p7nTCCK3ejvha4z/z/sI4qP0YGwXzzuZPNfVUCd3Z1nTCmQn2Eke1wGt6fGZ5ZJv9jvranYyw3sgJjbqvVfNxq1vNr8/HTzX0+FY7Xyc/2h/DI4tgd6tTWiq9EArT2vHHcf7A288X8EJgY7nJF+s380N+CkeI0A2OtlU5NSXuk3zBSVmvg+HCX5Ui4YWTMewLjKngdxtzTh4C4cJdNbu16XW82v+DdV05/Eu4ytVBWHeD2gMc2CmM5mDzz8/QbYLLPflIx5qNUmrc3gN7hrp9ZNq82SqTWJ9h3WqTVK5TPv+5eJ4zhcf7+fl7tyPJj9AqvMveRB9xPJ7VnWqoTRiAd6DNjvsc+YoGnMIYU1wKf4pF+3txmGEaHRK253ZNAbDheJz/bH6J5gBbWOinzAEIIIYQQQgghwkzmPQghhBBCCCFENyEBmhBCCCGEEEJ0ExKgCSGEEEIIIUQ3IQGaEEIIIYQQQnQTEqAJIYQQQgghRDchAZoQQgghhBBCdBMSoAkhhBBCCCFENyEBmhBCCCGEEEJ0ExKgCSGEEEIIIUQ3IQGaEEIIIYQQQnQTEqAJIYQQQgghRDchAZoQJqXUXKWUVkrNDXdZhBBCiO5Cvh+F6FpKax3uMgjRLSilkoGJwE6tdWW4yyOEEEJ0B/L9KETXkgBNCCGEEEIIIboJGeIoehSl1Fil1P+UUoVKqXql1GGl1PtKqSh/QziUUlal1INKqTylVK1S6mul1Hhzuwc8tnvAvG+8UupzpVSNue+rzcd/pZTarZSqVkqtUEod5VOuy819F5nbbFJKXdVV50UIIUTPJt+PQnQfUeEugBBdbDFQBtwEFAODgXMIfLHir8CfgEeAr4DpwCct7P994EXg38DNwMtKqTHAXOBuIBpYALwFnODxvFHAB8A/ARfwE+C/Sql4rfVzra2kEEII0Ury/ShENyEBmugxlFJpwGjgQq2155fIW+bjvtunArcDz2mt7zLv/lIpZQMeDXCYR7TWr5vPXw+cD9wAjHSP21dKDQQWKKWGa60zAbTWD3kc1wKsBAZifFHKF5AQQohOI9+PQnQvMsRR9CQlwAHgn0qp68wrdy2ZAiRgXPXz9EELz1nq/o/WugwoBL73mVS92/w51H2HUmqMUuptpVQOYDdvvwHGBSmjEEII0V7y/ShENyIBmugxtJER5wxgPfAPIEMpdUApdVOApww0fxb63F/QwmHKfH63BbgPIA5AKZUIfAkcgzHMYzYwA3gZiG3hWEIIIUS7yfejEN2LDHEUPYrW+gDwa2WM1zgGuBV4Vil1CKjz2TzP/Nkf2OFxf3oHF2smMByYrbX+zn2nUkr+PoUQQnQJ+X4UovuQHjTRI2nDZuAO867JfjbbBtQAP/O53/f39upl/rS77zDH91/YwccRQgghWiTfj0KEn1yBED2GUupojAxR7wL7ACswH3AAXwNJnttrrcuUUk8Af1JKVWFkqZoGXGtu4uqgoq0BKoFnlFL3Y4zrvxcji1ZKBx1DCCGE8Eu+H4XoXiRAEz1JPnAY46rgEKAe4yrgeVrrDZ7ru3i4H1AYXzq/A9ZhfGmtBio6olBa6yKl1MUYma8+AHIxvij7mMcXQgghOpN8PwrRjShjXqgQIlRKqXkYmat+orX+NtzlEUIIIboD+X4UomNIgCZEC5RSJwDnYlwZrMdYiPNuYA9wkpY/ICGEED2QfD8K0XlkiKMQLasGfgLcAiRjpBR+D7hHvnyEEEL0YPL9KEQnkR40IYQQQgghhOgmJM2+EEIIIYQQQnQTrRrimJaWpkeMGNFJRRFCCHGk2bBhQ7HWul+4y9EV5DtSCCFEqFr6fmxVgDZixAjWr1/fMaUSQghxxFNKZYa7DF1FviOFEEKEqqXvRxniKIQQQgghhBDdhARoQgghhBBCCNFNSJr9bsrhdPHDoVLW7i9hS1Y5WWV1VNXZibIqUuKjGZgSzwmj+nDa+HSGp/UiNsoa7iILIYTwZK8HZwPEpYS7JEKIttr2ASSkwai54S6J6EEkQOtmiqoaWLj2EG+uy6Skxg6ARYHLYzWE/MoG9hRUszKjiIeX7UEpGNM/kWOHpnLCqD6cMq4/qQkx4amAEEIIQ8YycDlgyrxwl0QI0R41xeEugehhJEDrJmoaHDy/6gAvfLOfeoeLKIsCYEBKHHPH9uOYob0Z3qcXCbFRRFstNDicrNlfzBc7C9maVc6+wmoOl9by7vosLAqmD09l3vQhXHDMYOJjpHdNCCG6nMsR7hIIIYSIQBKgdQMr9xTy5/9tJ6e8jtgoY1rg6RPSuXb2SI4bnopSyu/zjh2Wyi2njCGrtJZ/Lt3N4m15jOybwKwxffn+QCl3fbiNh5bs5vIZQ7nuJ6NIS4ztymoJIYQQQgghWkkCtDCyO138a9luXvz2IMlxxksxun8if794ClOH9g55P0P79OKZK6dx4Y587l60jUUbc3jisqkkxUezcG0mL357gDe+z+S208dw7axRWC3+Az4hhBDCr+J94LRB+sRwl0QIIY54ksUxTAor67nyxXW8+O1B0pNiqax3cOOco/jolpNbFZx5OnPSAJb8bjaj+iVy/RsbyCio4pkrp/HlHXOYeVRfHlqym3nPrWFfYXUH10YIIURAWgffprvL2wyFO8NdCiGE6BEkQAuDzVnlnPvUd2zNLmdw73hKa20suHwqd589nmirz0vicoHTHvIX/ICUON67YSanjU/nvo938MyKfRzVL5EXf30cCy6fysHiGs558lsWbczuhJoJIYRoxuUMdwmEEEJEEBni2MW+21vM9QvXk9ormiGpvcgqq+W/V81gzth+YKuFg6uMW/5WKN4LtcXmRHMF8amQNBDSRkPyYEgZAnGp4LJBdAIk9IV+44lPGsh/fjmNP7y/hUc+30OvGCtXnzySC6cOZuZRfbnt7c3c8d4WMgqq+cNPx8mQRyGE6EzaSY/4um2ohqg4sPaAugohRCeST9EutGRbHre9s4lRaQkkxkaxNaeCF399HHMSsuCjB2DHIrDXQlQ8DJgMo0+HpHTj9/pKyFkPxRnmMJMWetQS+hM98ic8OuEs7PWD+OunO+mTEMOFUwfTPymO1689ngc+2cFz3+xnf1E1T/3iWOKiJdOjEEJ0Cu0Kdwm6RsYy40Li6NPCXRIhhIhoEqB1kffWZ3H3h1uZNiyVUf0SeG99No+fnc7cjbfDnsUQkwhTfgaTLoLhJ0OUmXGxZD+sXgBb3jEWPO1zFEy6GPqNM9blyN0Eh9dCQyUkpMOQ48ASBQdXYd3+AU/HJHJ+n1N49L08UuIvYO64/kRbLfz94imMTU/i/k92cOMbG3jul9MlSBNCiM4Q4hDHwqp61u4vYeaovvRPjuvkQnWSurJwl0AIISKeBGhd4OPNOdz14VZmjU7jlHH9+dtnO7lhZDEXf3MVRMfDqffCCTdCbFLTk6qLYOU/YMOrRsA19QqYfhUMnAq+afeddti9GH54wQj2ouJhxrUw7CTUrk/46Y5FnBnzGYvfXETG5f9g7MRjALjqpBHERVu468NtEqQJIURn0aEFaDtyKgFYe6CEC6cO7swSCSGE6MYkQOtky7bnccd7WzhxZF9unHMUV728jlN7HeSPuffC5Ivh7H9BYr+mJ2gNW96GZXcb4/lnXAuz74SkAYEPYo02et4mXQT522Ht07D2Gdi0EGb9P9QpG6hb+yKn//A80e/Npf7oK4k77R5IGcxlM4YBcNeH27jlzY08/6vpRPkmKhFCCNF2oQ5xlOnAQgghkCyOnWrFnkJ++/YmjhmSwuOXHcMf313PYIpYYHkM67z/ws9e8Q7Oakvh7V/ARzdB/4lw81o455GWgzNfAybDxc/BTath2Ez46gF45Wx6jZ7FwSu+4y3XmURtfRv99HHw7WPgsHHZjGE8eNFklu8u5C8fb0cfCSmhhRCiu3CFFqBZfEdHCCGE6JEkQOskW7LKuemNDYwbkMQrVx/Pv97/hvwqG4/3fo+k6z6DKfO8n5C9AZ6bDfu+gp8+BPOXGPPM2ip9ElzxLsxfbAydfOvnTNz6MKln/Zm5DY+yO2EGLP8r/Ock2L+CX544nFtPGc3bP2Tx1Nf72ld5IYQQoMyv2BCHOPao8ExrqMoPdylEGGSV1rLxsMxVFKIlEqB1gqzSWq59bT1pibG8Mv94Vq36mkX7nPw2ZTXTbnoZ0id6P2Hnx/DqOWCxwLVfwMxbjP93hBGz4IZVMPdPsPNjzv/2Qm4fX8HZ+Tew5sTnjBT+Cy+CRddz5+x+XDJtMI99mcH767M65vhCCNFTNQZoofWg9agOtKI9cOg7qMwNd0kil9ZQuBucjnCXpFU2Hi4jq7Q23MUQoluTAK2DVdTZufrVH7E5nLx69Qx05lr+vKKCqTE53Pq7u7yHK2oN3z0B7/0aBhwN162AwdM6vlBRMTD3LrjxO+h7FPMO3serqS/z29Vx7J33Jfzkj7D9Q9QzJ/CvSYeZNTqNexZtY82+4o4vixBC9BTuAC3ELI49anS5rcb4aa8LbzkiWUU2FGw31k0VQhxRJEDrQHani5vf3EBmSQ3P/+o4RrsO8cA7q6gnlsd+cw5RCX2aNnY64NPb4Kv7YdIlcNUnkJDWuQXsPx6uXgZz7mZO/dd8ZL2bx9/8HzUn32UEh0kDiHr/V7yS+AxT+zi48Y0N7Cus6twyCSHEkcrdJRbiEEdXj4rQRLu531chXgAQ7SR/n6ILSYDWgf65dDer95Xwj0uOZma/Br58+QGWOKZz29xhjBo2pGlDpx0WXQcbX4NZd8ClLxnp9ruCNQpOuQc1fwn9EywsqLmbpS89gE6fDNd9DafeS/TepbzruI2zLeu4+tUfKa5u6JqyCSHEkaSVQxyl+SdENyYBmuhCEqB1kI835/DSdweZf9II5h2dRvVbV3Ff1UWM6xvN9Wcc07ShwwYfXAM7FsEZf4PT7++4+WatMXwmsbeuJSttFvMKn+Lgf39lBI4/+QPcsApr35E87HqUO6sf47ZXv6HeLlfohBCiVVo5xDGiI7TWNl570nw7cWQIsSdciI4gAVoH2J1fyd0fbmPGiFT+fM54WHIn/84aT77uw0M/n0G0e10xRwO8Px92fWJkajz5trCWm/jejLj5fyxKmc+InMXUPX8alB2C/hPgmi9g7j1cYF3Dw0U38cxrC3G5Irn1IIQQXazVPWjyGSuOLA6niwbHERLYhLqeoRAdQAK0dqqst3Pjwg0kxkXxzBXTiN76Jrs2fMPrzp9y5YnDmD481djQ6YD3r4Y9i+HsR4xMjd2AxWrllOsf4Y8xf8ZRkonr+Tmwb7kxFHLu3ViuWUZyfBy3Z93O9/+93ehlE0IIEQL3HLTQAq/kuGjjWT0qnWNge/KrWLotL9zFECEqqKynpsE7o+Q3GUUs2+5/OYWIW3M1XAFa/nbY9kF4ji3CRgK0dtBa8+f/bSerrI5nr5xGf3sOesld/C3qdyTHx/D7M8e5N4RPf2cGZ/+CE64Pb8F9pCbEcOWvfsNF9r+T40xFv3GpkV1Saxh6PEm3r2Vzn7M5KfdVSp6cA6UHwl1kIYTo/lqZJCQu2grAwJS4zipR5+mExvbu/EpsTum1iBTfHyhh+e5Cr/uqGwIvARBp8VnYArSi3eE5rggrCdDaYdHGHD7dkssdZ4xlxtAkWHQdn7tmsLZ2MHecOZbevWKMDb+8Dza/CXPuhhNuCG+hAzh2WCq/OmcuZ1b9hX39zjCyS350EzgaUHHJHHPrmzyVdh9R5Ydw/Gc27PhfuIsshBDdnDtAC3GIY6Q1WNulZ/QSZpXWklveeUsJFFbVU1nffUa2tKZXLOKylsoQR9GFJEBro0PFNdz38XZOGNmHG+ccBaseoT57K3+3XM/Y9ESuOH6YseHqBbDmSZhxHcy9O7yFDuKqk0Zw6tEjOStnPtnH3A5b3obXLoDqIqKsFub/5nf8NuVJdtgGGnPpFt8J9vpwF1sIIbq3EBuiMgftyLPxcBk/HirttP0fLq1lc1Z5p+0/VG2Zox5x73YJ0EQXkgCtDexOF7e9uxmrRfH4ZVOx5vwIq/7NS/3uJqtacf/5k4iyWmDr+0bv2aRLjKGN3XxegVKKhy89muF9Erh452wqznsR8rbAi6dCwQ6S4qL55zXnclP0//GW9UL48b/wyllQkRPuogshREBKqZuVUgeVUvVKqQ1KqdkhPm+WUsqhlNretiObTdAQhzi647hI61gwRGShRQdxtuFNG3k9aF1Y3vIsKNnfdcfryUr2Q11ZuEvRjARobfDU1/vYklXOPy45mkG9XLDoegoSx/NMwSTOmJjOyaPTIOsH+PgWGD4LLn4+PKn02yAxNopnfzmNqno7N24chnP+EnDZ4aUzYc9SBvWO54WrT+L/bFfw96R70cUZ8MJcOLwu3EUXQohmlFKXAQuAh4BjgTXAUqXUsCDPSwVeB5a3+eCNEZesgxZQpDXSu6mS6gYqasM31NHZlh60iHvpO6jALmfwgCBrHeRu8jl8xJ2w7s9WY5znfW3/mO8skRE1dCM7cit4dsU+Lj52MOcePRC+eRjKDvKv1AdwuODP50yA8sPwzhWQPAguWwhRMeEudquMH5DMgxdNYe2BEh7fkWAsYN13NLz9C1j9JJMHJfPUL47l5ZJJ3Jn8KK6YRHj1XNjwWriLLoQQvu4AXtVav6i13qW1/i2QB9wU5HkvAa8Ba9t+6FYGaGYDLOKy2wXgcmlZQ7MNSmts7MqrbNVzvttXzMqMwuAbdpJgAZos0+Mhe70REDgagm/rsHV+eXqyjM/DXYKAJEBrBbvTxR8/2ErvXjHcf/5EKNgBa59h+9hb+DDDztWzRjAiyQVvXW78UV3xHvTqE+5it8m86UO47LihPL1iHyvyouDqpTDxQvjyL/DxrZw+tjdPXDaVj3KSuS72YZzDZxmZKr/4C7hknLYQIvyUUjHAdOALn4e+AE5q4Xk3A+nAg+0qQCvHLHbbNmwo5fezzbacCj7fkY/DXybGbj7kP5y+3VtERkFV5x7EaYeijA7rlQk4xFFDnc3pdzhjxA1x7Ch15pzEUJYtytvc9P+eer46UzeeVygBWiu8sOoAO3IrefCiSfSOi4LP/h/EpfBw9Tn07hXNzXNGwYfXGSlRf/4q9Bsb7iK3y18vnMSEgcn8v3c3k1OrYN4rRibKzW/A6xdy/ugYHr9sKisy7fy64Q84pv/GSIiy6DehXRkSQojOlQZYgQKf+wuAAf6eoJSaAtwP/FLr4JPHlFLXK6XWK6XWVxRmG8OXfIXcCOimDbA2NgzzKowkUo5uG3n2YHlbIX8rVPmsM6d1m3ptAvWQ5ZTXsTOvkoq65sFIxMUbHVbgVmR39fw8qSuTxGxHgIo6O8XVwdvIEqCFaF9hFQu+2su5UwZy1uSBsGkhZK1j9dH/4NsDFdx6ymhSflwAGUvhrH/AUaeGu8jtFhdt5dkrp+F0am5YuJ4auwtOuQcufckYs/viqVw4qIpHf34Maw6WMz//Z9hPuR+2fwgLL4G68GeWEkKIUCmlYoF3gd9rrQ+G8hyt9Qta6+O01selJCX4zC1p7RBHr2d1I6GUqPk2FrMd2nJPSfB9HylDPrsVl7k+mW8vTvaPsOuToE9fsaeQzJKaxt8DDXGstRnHqfMz1LXH9aDVFEN9BSh307uVf1cHVsDe7jskr9OUHgBn4PX0Is3KPYWs3lccdDsJ0ELgcmnu+nAbCbFWHrhgElQXwZf34Ro2i3/uHcTg3vH8ut9eWPEQHH0ZHN+9FqJuj5FpCTz5i2PZmVvJLW9tNIaqTJkH85eAvQ5eOpOLkzN4ZN4xrD5Qwq/3nET9+c8ZE1xfOcc4V0IIER7FgBNjuKKndCDfz/YDgQnAK2b2RgdwHzDJ/P3MkI/stBsT0CHyk4S0cRiQxRzG2NPa4R0l9MC0DSfYVm0+1SdwKj/sPniLT6+ss3ul9w80xNF9r7+He9zb4sBK2PulxwL2bfi7CmVY5JGkqgByNhoZxXsYCdBC8OHGbDZklvGncybQLynWmIdlq2HJ2L+yLaeSP5/ci5iProf0SXDeE0fc2PpTxvfnwYumsHJPEfd+tN340hgyHa5bDilD4I15zHN9zuM/n8oPh0q5Yt0wqn/2jnHV49VzocpfO0gIITqX1toGbADO8HnoDIxsjr5ygCnAVI/bc8A+8//+nuOfral3IeR10FozZa0rRygEK5DWcOCbZpnpVEg9aO0/fMTR2kjt7XJRWmMLuNB08NPejhPjfq0CzRlv5b7dPWjKp/3T9J5uvr8j7nUNVWOA1lNPQCu4e3odHTC0sygjopKuSIAWREWtnX8u3c20Yb25dNoQOLgKtryNfeZt/HttFVP6x3D2zj8af2iXLYSYXuEucqe44oRh3HrKaN75MYsnl+8z7uw9DK5ZBqNPg8V3cFHB0zxz+TFsy6ng8q9iqZz3NlRkGz1pslaaECI8HgPmK6V+o5SaoJRaAAzCCLxQSr2ulHodQGtt11pv97wBhUCD+Xt18MO5o5JOHJKTvw32fQX1rcv013ZBGpIuhzF8q2Sf193uHjT36LfqBs9z4t2Qtzlc7M6v9GrIx9YXo1yOsPS07Mmvoqahk17D8kxjmkDRLr7dW8SK3f6zLward6jte6114CyKgaZZtrJ3pzFAC/C4b+DWo7mHOEqAFlzj+0Yb8/FyN7dtuGN1oTHn0nfpgvZy2pt6nTuYBGhBPPblHspqbfztwslYXDb47A5IHcE7vS7nUEktz/V7H5W3BS55AfqMCndxO9WdZ47lkmmDefyrDF5cdcC4My4ZLn8bTrgRvn+Ws7bfwQuXT2JvQTXzlloovfRd4w/j1XOMhReFEKILaa3fBW4H7gU2A7OAc7TWmeYmw8xbx/IaihRqD5qZZj/I9rai/WSW1OAKJWNu5pr2j2II2pD03/j2bFtlldayfFcBhVX+r4Tvzq9kT34VOeV1xh22GtKK15FatrVtZW5BRZ2djzfnUBWg56qmwcHu/Ep+OFhqJGXY9kHHDtd3NzCd7bua3/SqtBz8rN5Xwqdbc/0/6C+pDbQ6QHO/FX3jMM+4sM7mc6xIiE883/ttCagcDX56KVsxxLEzgjhHAzR0cpbQDuPR21i817gIVJzR+t24P49DuHCWWVIT+vIg2euNdY/rK1pfpiAkQGvBjtwKFn6fyS9PHM7kwSmw+kko2UvNGf9mwYpMbhuwncH734WTb4dxZ4W7uJ1OKcW/Lj2ac6cM5O9LdvHfb80gzRoFZz8M5/wb9n7JKd9dySs/G0F2WR2Xfuak6JJ3obYMXr/AGE8shBBdSGv9rNZ6hNY6Vms9XWu9yuOxuVrruS089wGt9eRWH9RlNggsUR3eyDpcUkVRdQOFwTKBaQ2VuXDou3YeMWhfjt9tVGMPmqbcXES5ut6ngdS49pvxq91p/sdsUEXZqzo8SUhehREEZpfVtbid06WbUqK3pVHYTh2VRKOkxnif+D2PvkGCZ1TtqabEeC8F4DCDENUsWDT2U1BZzxc78wMG6O1RZ3Py8eackDLjtUp9pRGct3U4sdaw61PIWe99f6uShHSC3Yu91/+qKYG9XwUO1sPJ8/3ofq+2Ze6eu6fYYm1xszqbk81Z5fx4qDS0/dprjZ8+vXrODlgDUgK0ALTW3PfxDlJ7xXDnGeOM8eKrHoFJF/NS3gjiarL4Xc1TMPg4OPXecBe3y0RZLTxx+VTOnjyABxfv4pXVHonOjr8OrnwPyjM56csLWXhBCsVVDVz0UQP5579hBGcLL4LaEN/4QggRSTwbwO4rttYYQu5Ba+1hfBvcLpd3Gu6OCmxCmYPmh2cWR3ewYQkw1M1qbuz07W1Qyvu8VGRDpU9q+NpSyNnQchk9xEcbjTR/mQU9GcsDtCOhQ0ChvS75FfV8uiXX/zpytH7dvO/8ZY5r1qMQoL4HVhi9sfgP9Nxl8X153Vvmm0suNNib9ltrd7B0W17AOXi+KursfrNFFlUZgdnh0tqQ9uOppLqBT7bk+m9MV5sXlOvdAZqfE+5yBR5q7D5PvkPg2pMkpCO4j+u0G4FF3iajjp3QC9R+HTQ01h18qpYDNLv5+WMP8DfXTIALGqv3FfP5jvaNXJAALYBPt+axIbOMP541jpT4KFjye7DGUDLrb7y8KoOFyc9htVhg3stgjQ53cbtUtNXCk784lrMmDeCvn+7kyeV7mz6wR58O134BUbFMX3Yxb51WR43NwYWf2Mg5+2Uj0H3jki6cOyGEEF3EXtv0he3+f3RcyE9vCrxa3k4F2iDre9j9meceQz52i4I2JAMFaE1z0NxbBJqKFG01miNNa6b5CXYBDn8Pmau9n3xgJZQeDLkHIMo8VsB5WaYGh9MocOEuOPhNSPsOZn9RdchX1vfkV+HSmpoG/9u3Nv4urfEzpDLQa+uzc5fWzeYHxtUVeGweaI6b8aPBYdQhNqqp2ZlbXo/N6eJQcY2/Z3qptztZuaeQLdnNe7PcQ4Lb0pTfX1SD1tr/uXHUA7rlNl7uJtj7RevWfm2cgxZKENCJvWw7P4ZdH3fe/jtSey82uc+1peWwx/2ZEOhCUnP+E76U1bY/GYkEaH7U2508vHQ3EwYmM2/6UNixCPZ/Daf9hafXV3GT8y1GNuyGC56E1OHhLm5YRFstPHXFsVwybTCPfZnBPYu2NV3l6z8BfvM1DJjClK+v4t3j9uB0aS5YbCXrjOeMCe5vArIc2wAAIABJREFUXQa21l/tEkKIiGCvg6h4QLW/cVGZC7Wl5JbX+czj0c2389SuLH+eDWFtZOVtcZifbnY8dxNn2fa8xjWzAjV89hZUsfFwGQ6n9z6i7VWonR837zXzOnQH9URo3SzIczhd0FDZIe3keruT7TkVXunpW7Ijt4Iq3yGhbrWlqJwf21YQz17KZkMc/QcPGw+XcdAMpLSGtOJ19C3xGbpH82GZLc2n1EF6VT25ezTK/ARS7kO2JxGJ36e6M/5ZogI/scacm+h3PmGAuoc7SUhFdlMWT629i+loCNtUFIfTxQ8HS70/4zx7qNqTaMb9fg7Sg+a+QBQVJJBrFGhIcAtcLh1SAiIJ0Px4dc0hcsrruPfcCVhtlbDsHhg4layjrmD/usXcEPUZTL8aJl0U7qKGVbTVwqM/O4bfnmpkd7zu9fVNb7rEfnDVpzB5HuN+uJf3Rn9JTJSF8z5P5NCcJ+DwWnj3ytZddRJCiEjhchoNO6UIfYhjgO0y18D+r/nxUCnfZLQiWYWrjWsmVRUYWSJLzXnGWhsNUZ80+o0CNDQ956D5edDr15zyOnSANpgGqPGf6dBtb2EVueWhXfRrSsbio2A77PifV5BmawwYjUZVSXvmOVVkQX2VRw9ayw3OWpvTazFoL+1J/OIZfPn2OrYw/K60hV4Bh0tTa3M0fyuYv7t8fkJT5sfQeytaeH/Qth60luc3+jzW0rZ+5/cF2r6FIY4NVbB7SVPA1xlBXGWOz8UWj/Gpmavh0LdhWRg6t7yevIo6dud7jrDq4CGOFivkbQ041aaxBy3k6Kj1SyYcLqtld35V4yLugUiA5qOkuoFnvt7HqeP7c/LoNFj+f8YX0/lP8Oznm3jY+h8cqaPhpw+Fu6jdglKKO88cx0MXT+GbjCIueXZN03CF6Di49L8w+/eM2v087w14g+Q4K+d93Z8DJ/3D6JX84JojaoV4IYQwtOGKr/b64VeDw0lJVQO1DY7AW7obC7sXm/tT7M6vbBxmFpTd/Ax3N2ICpWJvOmBo+wUsFt9zEqQOgX43VeQfpLzBRUWdnfWHSkIqQ8C2VKk5p9ojsLUd+r7x/1/vLvQ/jytUWeuhaJffeVQhsdc3lZF2dOp5Bgbu17a+Eg6t9gjYWuj58nPfjtwKduVVNZu701IZ3achlMZwi2GU+YIGm1PYkubJTbwfbZtAPWgt9LoU7zWGR/sEEIVV9dTZjQsEHZ4MpalgTdkdwzA/zv0+8L6g4/5QbLrvUGlN47zDg8U1AbOxevGsT3GGMafSV1V+44Lr1lA/u9vQg1ZrDlluljDJhwRoPhYs30ut3cmfzhlvTDr+8b8w4zp2MIoTdv+D/pYKoua9eMSud9ZWV5wwjNevOYGCqnouePo7Vuwxr3YqBaf9Bc59jKGHP+L95AX0T4zinG9HcGD6vcZ8ic9uD19XvxBCdAbtTjDRAUMc8b7SX1TdQFF5JdayAy0cu0llvZ09+VVszQ4xCYB7SFfZIWPO14ZXgxXO/R//D3vuug1tXb97rczFueU9vtmZzbJMY6fx0T5NGnud33PfmpfDVec+Z02JTlqdVVIDxXvbP0py/9dG74bNp1dNa2IaWpF8q9TjfeNy4nJpXNkboCovpEx5/upfUWc0NktrbHy8OadxNI32eY5nL7FX4pjywyENrfMXSLn3WFDZ+gyRXjWx+2T19B2uqV3NE7a01JBvXKXbZWRKDPR4CA6X1rIzt4qDJTWsbuEiQSjvzQa703tNQq/nhJbApNbmoKKujT30AViUIqahDJfNX6IjbVygqC3hYFENa/YXo7Vma3Y53+31l/zG1fLFf3/nqaa48eKJ1eODqrLe3kJvV9sTvgQbDSEBmof9RdW8ue4wVxw/jNF94+HT2yExHU69l28+fI6LrGuwn/wHGDwt3EXtlmaNSePTW2cxJLUX17z6I49/mdH0YTbjWrjsDQaUrOPdqAcY0Tuas9ZN5uDEm2DTQlj+17CWXQghOpY247PWDHE0fwbZXKHpVZdHdNHOEMtiNCJCzkzmOeemIrvF9OqG0BuaLfdUtOIYBTvZk19FlLOOBodRr74JMU1bV+ZTv30xFDY/R0HXmXM42ZBZRnFVA7qxAUZjI8zr9WmopjJ7l98kE1prSqpt2KuLsedsIaemncO1MtcYc7gbgyjjR6/abIZlLmL4wXdD209FdtP/qwtYsaeQdft9hky28Cb094g7MCivtaE1lLsb7y10hLoDNAXGWlKHvg18zFaOLgxVbMVBYuuLsNQVGT3OXuu1GvMqKxqc5JbXsTuvisXb8gIklzHuqzeDn3LP4aClB3x6bHx6XSqyYc8y0Jpau9PnvaQ9/tdyRZdtz+OtdYcDZv3MKq2lzuYkp7yOQp9g1uF0kVFY7XW0lny5s4CVX30GmWtb3K41rBbF4KzP6H1wsce9Hj1oWeuMddB82PzVd/9y2PlR8/uDDGl1L/PhTloEsGJ3IV/uNC8e5G8ja/8u1riD5FbOJ/QMoB1B1rGUAM3DY19kEBdl4bbTx8CPLxqrjp/9T9bvPcyVxU9QkDyFuFP+EO5idmtD+/Tiw5tO4uJjB7Ng+V4uf+F7ssvMeQHjz4Vff0I/WxbvOO5gfB8rZ2yeTebIy+C7x2HNU+EtvBBCtJcKMCchd1NjmvK2aFUbtLoQcjYZ/3faQp6LllVaazTuWkqK4LdwTaWrd8LHm3MCZuZr6nDwPk/uXWSV1Dbbp7/jUFdGbX0DoBrvtihjDond6WJ7ZgGfZ1uxVTXvuWipLdXgcLJ8t3FlO7+ynvLG0WS6qeeqPNNYH8teDwdXsWLTbr7dbSYxqa9sHCaWX1nPoZIaSqtq2VpiYUdZ69e/0hBwhJ27wR7lqCW+Lh9LqHMOk9Ipa4CsamPH1Q0OlO9ctIIdoe3LVuu1iLdSCq11syDG3RT1vLdxDloo3aoaiqsajIsM9ZVtWgjen4SSbaQV/4DVnWK+cCfUlaG1xu5wAZq9xTZyK+rILDVef5dPj5NLa8rNoOrzHfks31XANxlF1DSYZQyUEM29n+z1YKsGp50fD5VxoLi6TXVZf6iMPQVVfLQph3q7k32F1VTW23E4XXy92wjENx425pFq4EBxtdmTpskuqyV/32bKqsxEMC6Xd5AZQE1JDmD83RwuaV/it5jCbSTWZJJYvMXPo7rZcgWNyWGcNuPvsSKn6cGASwa0/F5xX8TyDNC85G/H/t2T1ObvMQ/euiGOn2wJdrGriQRopu05FSzelse1s0eR5iqBrx+E0aejx59P1Ce3EKOc9L7yFWNRZtGi+Bgrj/18Kk9cNpXd+VWcveBbPnW/KYedANd8Qe8YzRt1NzO1v5XTdp9P7qCfwhf3wua3wlt4IYToENq8umoOcSzZH7Qnql0jIfO3GUmX6irg0CrjBjRkrqdy37rGIgVSWmNj4+EytuYEGQbpO7zOvWP3PCBzJJB7TaqQ5ofQFGzsL65pPkzL/LWyrh6b2VtGwXYoz0RjAa2JrisGl5N1B0tZsi2PgirjuDa7nQNF1WR5rJHl3ntJdUOzoUue63QBZFRazaSH2ki3X1+Js8QcIthQ1Tz43fkxbHjNOBdmNjqX09F4XgLWvw0vvt+n+A7T88cSxao8KxuLm5qAFu1TwOoC/wdwubzvzljqtQSBAnRDNa69X/usyecus0cfTWNgHSBAa6hqnHNX3WAns7SWvYXVRlr7Ayub7adtPLv0HMbf0cFv2ZpdwZIDNnPfGhqqvbctPQgHjR6/3PI6Vu8vbjbkzxlo2FtLjfp2VKbxmQpqGhzsyK3gmz1FbM+tJKe8jn2FTYGfUxt/8/sLq0BrXECvulysJbvB5WD//gy+2ZlNeUVVi8fcUmK8h348WMamrDKfLLOmnZ/AvuVByx+dY1zA8jpr7nPocjT9rfkm+XEHwGWHvHdoqzZfN8/9tVwG9+eL1eeiQZ/i9bDtQ3AaV2wSatw9rco4jvm5WFZj816MvSI7wGdmcBKgmf71+R5694rmutkjYdndxpvhnH+z85NHmWrfzI4pdxObPibcxYwoFx07mKW3zWZM/0R++/Ymfv/+FuNqTb+xcO3nJKek8nrV9UxLj+LUg1dQ1G8mfHwr7Fka7qILIUTb+M2K56dVkLPR6OnyoNEkVB8iqs7/3IS0onXE1hd5zG0xf9aVQ9EeyNsMdaXG/WaG3LyK+sYhQJ6lyCmvY09+U+PLPdwm6BpdPj0r+RX17C1o2o+yeTeIMgqqvdqc/tqfVfV2r3TyTpemznfOh9as3J3P1pxy7x1ZFIn2YhwVOcSU7WtsHFmUUR+Xw8a2nIrGngPjqcZzd+VVsXKPx7kOECjoxn8ARz1LdlcYwxWdDb5bGT0w5Zmgm4ZLWVWAuXcex9uR28q1Qb3K6nFSPQIX6spg2wfENPhk3/R9j2qN8g3QwM8i1jSfa+PTA4oCyg/hcjR4LPDsf3ieuwctYP9ZxueNC5C70587nZrKejs7DxzG5dJkltSQZy6CHV+bC9khLFjub708pZoyJ7rs5JTVgstBbkUDBfm5uCrziK0vNuuCUa7qAlCq8W9mq88abY2BZ7P3lU8vu8PWuC9/Qg7ePTZz78mlNTaHq7FHM8p8I2rtu6X5m73euJi0fznW7HXU7f48pENXt5Q23mnzmwF2R26FV8ITa1mmT9k8eN3nHmqsvR/0PX8FOyBjmd8daa3ZV1jdbJihvfGz0vNDy8XgnGXG56tvgZQyjrPfGMK6am8Ra/d79Nof/r4xOG3tRRgJ0IDvD5SwKqOIm+ceRdLhFcYVsJ/8AVtDHaO3/Jvvo47j2ItuD3cxI9LQPr1474aZ/O60MSzamM25T35rrAGTPAjmL6FX2lBeqbyOo/tHc1rOdZT3ngjvzzeySQkhRASxueCz7WbQpTU/5Ln4eK8dyrObb1x6AA6uanZ37/Id9C5oPq9Da01sQzFpxT803ue3OVdTSPOWmm+jDNYfKvVJZ+11MO/f43p77M+72bDu/7P33uG2XWW9/2fMOVfb/ezTk5wSSCMJoRcpojSliKAYQZEiCgiCCPzQq/cKVx+McBUFEVBREC6i0kGKlEhJQoDUU3PaPnvvc3Yvq6816xj3jzHrKnvvIP4OJOv7PMlZe605xxxjzDHXer/jfd/ve3aNk0u1+JrWylFwmxtvVJ/7foZI3HjPcsbA86XiyHziyVPokLmcl96JTq5gKB+lBH5KXEBERlyPPI8o+q5huzit1BwoRaAUwm8jInISk+GA0fa5mKAcXhfa+Aqyu/oxqameY+jEpxHSQ6C6bMdOY+3MSoOplXsX2uYE2nNo+dF5KrtbH4puFNud+WWdBEXp6Qx8rSCYdDJ+WWl5OF6AlMGGuVCGECgpCRSZmlOxKZ22e8N/e/KSDoEHUVtgb+MoeWeZ2bUWLS+g6fqcPnYnJ2f1+CbX74Ty2ficI3NV5iodHsXqeV1Kwa7y5SMLLNcigpANW8xXzoBdZanhYhAQSBWvicyt89rozMruYte91l7PAS8f1d6fTNhmQuLuZUBs97tKpRQzO64tUucphQg0sRaNZQQSqTqO92yozbNt7c7MRERhn0EfEqILrmc3YU4vNzKCJwnd6tjRkb4uzdSBZL7TuwO9kSjY6mNrtsfR+Srny9n14QW9+q/fa7UaCS9Tndfs7Q1VSsXEPz01ObfCRfNf6dtfGBA0lFL8n/84wZ6xIi9+xA74whthx5XwmFdR/+dfp6EKBM96N2a/eNQBNoVlGrzhaVfwL6/4CfxA8fz33cJ7v3GaYGgHvOTzDO+5nA/WfpMrt+d56tJv0yhdBB97ga5VMcAAAwzwYwJfpvNTFAuRrRvuDKfxubOKE0vZ8CHDqSXEIEIqnKfUWsT0E4Oi4frcPVvWpCk8zvEDbp+p0HIT41CogLHqPdrwaa33rQEUX+/EF/WOfgSrsOG4u9CZv5QxypX2MKXGaXmNeNxSKWwvoLK2onONwi65a1PsXLmFht/tjYjeqbRd5kOD3IgMxp5Gsv5sZ+M4nPgSKgzFc3zJmZUGxtJhtq/fmTmjXKsx0jzHUEuHqTqBoOaolEdJt+lLycxak/bCcQIpmWzPMuysYnYStB69OrxZeGl8soKpb3DT2Qq1tQXMoI/sekgERJdSRzInthcgor+Xj+kQP9BhW6laa+Wmy3zFxnOafdIDU6GL8RVT74WXqLS8nufEiIhZOnR0+hZKd/4DB8rfYbh2NuE3gct45SiXrN+UbUMG2F7Av912jq8e1WP4/tl1vjO1GocZ3z01z+nlBuW2Np5Fh9pqwdaeVTdIbpxKzVvc97nbqbQcet3RTalV1EZIzJr25jlfGzaX/qNrRyB8O/5z47y/6NNaZ5fu+XeYuYWh9nwmLPa7U2ucW2/1rnmIlsP/2vEl5Nmb4fAnYq9jvo9t/Z/3LPPdqTW8QLJcz65vobKrSyml+9nHA1luutx8Zk3XMAzP9UMi1tlf15fk3CoqSDYxoufD81V8VctvgFLUbL+v2IfYoDxJ0d68nuX9nnXceM8yt8+Ued1TLqf47T+D6iw859043/hztteP80/b38DjHnr1he7mfQKPvnSSL/7OE/mZa/fwji+f4EUf+C7L/hC8+LMM73sIH6y/ggPbSvzs2u/SNobg//5iVg54gAEGGOBHHCL6sY4z2EX3xq5STDZOUZ+7R4c3hdg2/03GaiezBnAqnLHUXmCslhSYXak7TK819e54aAwsVm2qHkyvNTNhRaP1M7qpMzfq/9DGyWfvmssWQ1ZSh4CVZ7SB3pVsrwfztWNLfPnwgiaMSmWtQyUh8BA9RCu67TfF7qVvMl49Hv3J7TNlVqbuIEjJrjvtBnMti7vKRT47bXL7ShI+lm4yklqPPGiyh/GklN7BH/HW8QNFq61JXRRGN+IscXn7Lgq+JtBOEFBuulTbfsYoVetTcP77yZiBhq29LdWp2/ClYl/rCLsbh3saW72UH7cE6UPgsq05TcP/Acy4cE4M6YY5ghKBotYIvYlKaZI90x3JouwOr+vKiYzyoQ7oDT02SsXFygHqtq9JUh+4vkQe/bTO70pvVNTOI30HgcqEiiqA+gKlyqnswvKdWOAiCqH72vElvnR4kaYbcHKpzrfOVLXh34dD5cNpjfY50oe5azPcPltmsRZtlvTxXMXemD4hjimfEcCN9/Qy2jf3n62XywSnvh5vcqw13C7yGytmdpAYAeA2Ix97xweCk9Xs+mo6PrfNdG/wKGC57vRVmy+H90PVIlERfeC4cz7ZMDJzuq9mgZrtsViz+eI9ZW5bMTuUGrvn5D/nTTLzHBH9paPUmnqn7PzCHMGZb2RayMyGUvhum13LN1FavqP3QNIkvTLL3bOr2gsXzm+pOcfF578Q3guZ/VpMvRZKsuqYbIT7NUGTUnvPDm4f4vq9i3Dr++BRvwFA7jvv4l/9n+Jpv/DyrgU9wA+O8VKO97zwYbzj+ddx17kKz3jXt/nGjA0v+iQjD3wsH2q8kl0Tozy3+iZcz4UPPzezizfAAAMM8KMN/QPuSwlC6F3UVM7LUs2m0nTI+5FaYXaX1QycJMdl/s7YIPB9D1v2KvIc1ucKDYSmb3C0mqfsoAuydhw9V2nFwhjRLvLxhcSTp/OClCaWlRlYuScM1YHFVpKr1nR9imtH2LN4Y5cHZ7x9DmZvZXKmM/8D1ppOT2ISER9FmM+iyAgOeORp+Eac1+NnDMHQ+FQ6fNHxZezDkR0WowpDxu46l+QL/ceRBRaq7bidoqdJqXAjwhL9kzUMjVaKbKSVLKVAua2Q8OlOZc0IFddw2gh9TfMwdMrYtIB4t+2yUG2Dkoy259hbuQMjcFBSslSzma+6es5VKhxMBhljX3Ra4HYF6vMZgQqlRBhSl/aqgedLzpfb2pPRMT6pFIfmKsyuNfXa74igUYDEoO4ZnKjlkg+8NgoYaZzVgjEAgdslvR7nuynJQsOPywDYoSiMiEL9GksgffKmPj7liI7DBGVVqwkm4ZEw1Joj7+jco2JL15NT9GEr0W1ZuFurD/aAp2B1C2Xdmo7Pt+86xuHzFXJOmSGvzOj0V5B+dnMkDnFMVY2ALGETqXBKQ/RefZV2702FqBXj9H/o0N8+8IIwJy5cU+Nrh+INIxUStMAokXfWGa2divuaFQUNPWiJCy0ajH69ciIJdXUbWA2tsFq013CiHLPwnE6BmmjejHYZKZUm+uk1nwpDlVIilM7vk2FO21hdlwEwAzt+VnypmF1twLHPcvG5zyGki1AB51qpddwD92uC9vlD89yzWOcNTzmI9e+vh9G98IQ34n/yFcypHdzxoDfz4EvGL3Q373MQQnD9I/fx+dc+np2jBV76we9zw9dn8K7/Z0avfBL/1PwthiZ28ILmG/HrK/Dhn8/I+A4wwAAD/Kgi+lH+5rmwNlf1SObzW6fW+GavwqpKgZRItGjGyuxxVmeOxcbB6eU6M80cSphkdc4UavbW+LggzBlxOmz3nFtl+9TnWKjaHFvokXsW2jjlpjbUM3Cb1Fw43zQ4s5rkKBXb2sNlSC+zV2wGkWUZhf2FxlBgc+eZhURGvGOXX0hPkyClyVA7DINSqC4nnecH4fnJB5PrtwE69yjyEqU9aLYX8Lm751NqdolxdmqpgS8VthvE5G60cpLx8uHszncvgYmoHyFmmjmmKorA94nsXDNl8M6cn9N97AMRGpoj7nJ8PSlViixoQzqavojHLtkW9ch+bK3rUkEd+N7ZdVABI7Y2Wi0hqbY9Wo7PsmPqlqMxpsRm4iv3rAHWSSYTr2/sK0odUAsFYaK2lEo2C6qRWEwqlBcVKkcKg4JsMrJyB5aXzh3Ua0eoQNfKWj6G70fEK/INRQRNkWutMOFli2KbS4eSQQQeUc1zP7Upknhd9IfpfKuRxjQ7V25l++ptbF+/g9Ha6YRUbHmPP2nvWFlw86KJ7asNxSVabgAI6p5AodjTPk1O2ig7JYqTGr8hunxl+m8FU2tN1h2D21YMVu3e9MDxJLUwTDUdJhlXF7HrLJ47xWfvmut1OkfnaxyaqyScqrMTYd92rnxHRwvERCo6RMXPlP6uUAw158LvP6Fz+RYPZz2wcQh48uxG96bTAZO+p4fmqnzz5Er8na4A1s8k3Q0JGsBSQ+e0pRF9NrPe5tD0Aq3F00xUjlO0VzYMf4xwvyVoXiB551dP8qC9Yzy7/gmdpPmsv4Bv/ClG9RxvDl7Na5/5sAvdzfs0Lts1ymde83h+9TH7+dtvTvFLH7iDc099P6NXPZl/av4WcuwSXmK/EX99Gj78HGj2D40YYIABBvjRgEJJScPVBkPBq9LDHEpeRuE9SgKSZdtksWpzaEHX0IqIV9OOjCIjZe0qvettV+kXWyRD/lKwV/t6ZCbW7iR3Ptr1Vqy1fFAyNvwDp85aU3taHC+dmxESKCEyhntnztO5covlmsPeha9z+blPaLW9eMwJDOlzYO1mdi3+Z3qIYaO63plS0HZ9yi2HlheAEox63Rt4p5a0AR85Umwv4GPfnaXW9lDlWYbr06mj9UWmVhosVO1Y3EGgd8ezCnXJ2FpugC8lu2t3g5R4gcQJr+cGirG1uwEV5tHY8X0z6+exfU1pm33U7yyvzv76XVzc0AT/xFKdO1YNTdKURCkRG92zdU3ZzzVNbl4IzbqUWEYXNNsJx6hSXrHw3HRoqsrK6ov52zI5lbHzNjxmre7gteosVm2y67579e099wXGK7qQeOSZtTpdPCF0RTJBKdDe3kajQTnliVVKYURG+eopls/cmfnMi3OOJKPt81zcznqX+yHDR2MCIXD9ICSViUrrUPO8VmH1mgy1zmO7AScqqltoA6HzK1OL3PGCMNxUv9cIb8HJsuTEUp2cUyFvd4cWeoH21FuG7mz07M2uZd1v0T5FnB3YQZB8KUHBUmtjNjm12mStGeXt6UZOL9fjeVIo5sp20rcORGs2f/yTWF4jmzemoucunAPbj8cXk/n0/xWU2vNsqx1j1J7XbbktmLsNnO5NKBHu8iilWG04FNuLPaLPdduOH8Sh3zlPb+jUPLh7TcTbY2kvsZ3y9iulPY1CSZRSuOHaC5T+rtwq7rcE7d9uO8fMWou3/ISJ8a13wDXP0279Oz/C+/1n8+DH/SyXbBu60N28z6OYM3nb8x7M3/zKwzmz3OCZ7/0eX776Bsaufiofab2aYOIgL26/AX/1jPakbZTcPsAAAwxwgSFQqHu+GKvhSSNPy++wNlMWb+3kt7Sxds+/g1L4SmBIj+SUyPIJd3FF5892yMA6Q/mA21YMTtbyLNomea+/jHupOYfR0KRJKB0iuNKGr894HFtxqdk+bden5QUZlTNTJgp4/bMtNKphaFSpvUipvRTuasts3S5hUAgaWF6TyEsYtCqo87cTcQBFVnJdoMhJm5VUPkfJrzHaOMNaw+H0ch2URFbnaTTqrLdcxsqHKHjlrh43O92OAIJMfSvh6F1yLwhYbdis1l2swEa4dW46vcqJqhm3GLVv+wGVlov0PUbb5xFKYQQuy+dOc2J+nZbrc269FRuEacXAYkhIyi2XtYbDYt3TpCnbxUSxXQkCqVipOzpcr7FEEMg45wdAKUnMGZSMRRckQrcWl39Q2hORFgBRwMrx+O+pmuD21WTTYJc9xfjq7dTqlcx5Xep+KgAUw40Z1poOzTDsNq4/lV7PSmmiLRJJmNlmju+GcuZKRYa1luCfrgXMLiQlLM6vJ2usV05i6kKZv3J+g3yYh4hKhuMEsLy8SHl9maqnnxkhPYr2CqP1M5Qqp/AX7+FLRxb5yhmHW5cNautLrM3p8DddFuM4hPlYKMVcpc2ZlTpNx8fxgpg4zK61adg+o42zjDS7xYYikpgTIAi0V1sFTK8neaXF6hRCRqSq33C3Rhxib17q3I/cqvslpI9UaLJI+NxsMN8FJ9l0l1KFIhzE3uGVusNU6O1OhxebQYucW+HUpD2wAAAgAElEQVT2mTJmqJBoSF/Pa+D1LqNA4tFab7q0vYCCs4bR8XUardNKK9k42bmiczHnWwaeFLFXVZF40NJ109YaDtOrLVqOq3stjHjCov5uBfdLgmZ7Ae/++iketX+Mx9z1h5Afhie+EfW513E2dxn/YL2A1/zUZRe6m/crPOu6vXzhdU/kATuGedXHjvD24d9j+Jqf4UONVzG66yAvtd+Av3wS9eHnQHNt8wYHGGCAAS4ElELGBXoFUlicCVONeqn0nVyqg29rwyL0VhSaKVn+cBc2MlilMGLjSIQ7uDL1uQpdGunQrJpnhk1JJspHKLV6hx+FFwRgpqGNitV2Et7TcgP81K64bmtB7xSn7DCRMsZzbnbMGZtQSXDq5NwKVzZvw5C6MLAEVMQgWqF3LDT+ksAqbbKJVChkZGReVvsu25zz1GyPmqNVCrevfZ/95e9wcfn7CL+zmLNKtQhWGKKZDuFqR2p+YZ03N2bQ+l9RPkutnfU8Ra6lkPYw2pplrH2end4cq2vLBM01djRPstZwqVbWaFZW8QLJXbNllqrZPhZzJr5UrDaTdZK2lX1DK22aw9s5Nl/j2EKN2tI0lKeZWm1lQipVyoMGilE7XG+RtdpciQ6E01/LqBcCNGtJ7lzZ1e1Y6/cAMO5qYiRU0HPTIIIRGtFC+SysrHN0egnWzpDHI5CS26ZXMzLqOrxTbKIJoFitO9yz2Mh4JtteSthFydAbl+1Yte1pFcv4ONhVO8K21lTc99MrDZRdx5dQcCvQXMUJlf3iMDghmGtbrDtaXCYI53p1+gjVpZBgRWGj0fdEJOCBYna9zXzFju9OZ306peD4Qo1T55ao3PYJ3FYFhCBnKnJuhbxfo+isxc9P3lljaO0IO2rH4vEnl8zmRgqlSNdpN6SXENQOnF1tsh7mEo5XjjNWPc5E5QhKgRGuo8/cOcen75jpygeEVIhh+Pf3ptc5FkVlpr4/Is9qOt9sqLWAcebGjMcRIXQ+ZA/PWTI+veYiEiaNfObzpuMhww0o1TEv0LFm4jf0u66f3Ke4llpMTg36pPRtiPslQfunW6ZZqjm886KvI+bvgGf+OXz1j5Bui99ovJLXPPVqxoc2Tt4b4IeP/duH+PirHsevPfYA77tplpfXX4XxoGfzN+VXccnFl/Drzu/iL51AffAZUN3IwBhggAEG+P8fSkHerSGjcGwh9H/Sg3Pf4+TcKmdXmxkDBIh3fHNOmVagf5aP1wrctl7E833ttQp/7E2/M3QsVEhLGcOW8ntuiAeBjyE9Su1lxirHdc2jynlYS8K9RHudwG1iex2hd+El0x403dYiQmkPWt32mFlrkveqWt0x8Hnw8ucoBH3qeykJSlJe1/OVD1qxzaPIGkVmYykjJBIbTV2eGUneLWMFribLSoAKqLZ8PKdFwV6NpfI7JykhPPrFsKxRt31qnsmSbYVnZK8rjITodFpwdT/xLBWDGiq1s+/6sM1fYV/rHprri1xR/Q6X1b4bhgamxRgEKMiHOv2BEqEHTWXmKPKsCkMwNb8EIZEA8MPrnl5uIKUKhVJCmhtIdlSPhu0Y+FKGhm9qXmZuIfJoLtcdzkaqn25CIk2nhhE4WDKVsxa4mSkW5SlG6prwCBWg0CR/z+KNsWFtuTW8QBEEQfisaFXRdsgczEy9gmT8Uql4TZjKw3d1P0Zrp6kd/lJyRkyGEtTaHtOrzWTcGe9d8jLXWkLN3JLJAI08eklOkYhJTiGUkO+WtN/cWm+G5SQm6ycyR0ulcOw2n/zOUb65YNJamwMEpsi2Gr2OiPCws8R1q1/ECIuHq2icXqR62t2vnfVjXNo60v19FaIWlgUwAlt7kdFrK7pFa00XJWUsqR+h3HRx/QAhFaK1CtJnqWanLtOh2JgSL4n+rds+DSfQGxnhem57PnY7+a6p25rsR9/DUkrcIHs3ApnUZ9NlTxQT64cYL+vQ4mJ7Oc6pbdo+TSdbJiJac4tVm5m1Jsv1ZBwWQfhlpXse9b1oJ97djXC/I2jVtsd7v3GGFx+ssO/QX8O1z9e7RWdu5C+Nl2LsvJJf+4kDF7qb91vkLYM/ee613PALD+amqTLPmH0RrSufyw3Lr+HagxfxIvv3sNfPo/7h6bB66kJ3d4ABBhgghlSKbZXDiHQieZgzppRiqD1PsHCYbeVDZIyQMJzNDLTBG2282oHgK0cXORWG6YEOY0qyIBSNts/UWjtjVB60j2H73eRFhMqRdV9QrJxmW/UY1KN8MLQ09eppKuur1O2OnfvwX19JjsxVMwqLO1a/g2rXYo+HUoqx+mlMt0pB2exqn9UHOo0eLSoqTmgehuIYCtjTnooPcwM4vOxQd8PQxkxiUDLupi8wA5t8nPenONvMUWmGHjGlVfu6dS7CHXUlMVL5V5OhkMSKY+LIyBDPnmx7ocE/tJ1ORc5zTSt+vbt5iiDok2+mElJzJixWbYT3sxA0MRbvjomAH8V/dXL8SKUQRTB/GKqzXeOstj3uPl8Jjw3N1CAh/EoYrNYdHR4JejznvodaOETO054U202NoZ2kHBys38FDFj/BSHM67IeE+TszIiH1lXOMh966OO8tJJZShHMVhIIzIQnFa4MK8KU+Z9JOF31PvCsLVTc2tLe3pjjQvAuAorPCXDkJ91O+BwhK9lL8vPmhBzpeV4uH4ulNnrQUGUzfRwE5r54yuoUOFe0QjgGt7ml7AbhNXD/AkxJfyrgUQDQnebfMXLnNXLmN2+r2CJnKR4Z1us5WFQiRKT+QDYHVrwynynB7DmPtRPJudV4rtQYuQyt3YgV9Csx7nR5nDUv5nF9PnmlD+UgZxMWwBSERTz0zri+ptDxm1lr4rXUtBFfRqphSGMm8p86JBDZTAwRgcXmJcr2JH6qQHp2vcfeM3uxx/ICVusNqIwkpnGmYHFvRm1kqTM5drjscX9RzrAVUtDpqVG9y+9r3Ga0n3+et1PeeDpcNIxuAtXqbestJiJiv2/VzY5nvZ6NH+ZFeuN8RtL/95hnsdpM/cP4KhnbAo14OX30LZ7f/JO+pP5G3/Nw15AZFqS84Xvjo/XzsNx9L1YUnnLiehUufx5vnf4enXTHG89t/QK1RR/7jz2oZ6gEGGGCAHyEsJ0KHKCFwZJinA1zUPM5Q81xGIt3zdehgEx2m5opcyp0jwxC+0BBQWZJwYrlB4/yxuGZkQntEVxHWsZrOgZlv55irJLV7mo7OMdOGkuo6T8qUYLjSJOL0chT6pHPmVHk6Q5wEAVLo0MpSUKNUPZ0pfi0VLNe0IEdBhbv4oVclwz8UtIOoTRX3J0aqVtpC26LgJiHwkc26XMsamDmvRl62GWlMYUiXcsNltW4z3DzPUHvj6IxO9bWl8F4L34XKdPfxqddZYpmaq1Sxa2XX9aa7SBl066fx6ikhlEyYmoYXEshqy2e23KLheD2IaCQao1ChR2FutcJYaICmfQtSqbBGn4LquY6RoMl8SnJcICnKFqby4jF1bhDsdabYb5/AlC5C+VFwqL62odeKlBIp9btGSNhd36fl6hp0gqwYQzhrNG2bpZQxHkjJxLpWsRSpJD0ZePF5kaiIaZeRXpsVO6VKGOYK+VGsm0r+WT6WFMYWQjDSmKbg6Pi8tAiEUiqTmzTTzHFkdhnKZzlfbnNqucEtZ9aotD1WHDN+rvNejVJQ5aL63bpcRtBp0KdKLAiTpiM5Ml+L15Eg+wCdWWnQbumFur62RtULiVCYlxbVS8y5vcMZ8Xvr/R+0jzG6crueQ+VxeesujNpcZqWIjDcsgVQwtVLX5FQG4DsIGT7/ktiTHN0s29fFqLX3HFABY/XTDLXmaNgenoQl24wVQqNNLj/ajFAqzus1lg4zPz+LO38406f0OlHAzFqLNac/H5AoHF+y5JgopZgsHwrLPSgmnHmE9HQ4rZlDIHuGem6E+xUTWarZ/OPNZ3nvRV+mWD4Jz34nfOFNBIVRXrT8In7mmj084fIdF7qbA4R45MFJPv/ax3Nw5yhPOPGLHNv9HH5j5v/jldfCL7lvYbktkP/4TLjnCxe6qwMMMMAAIRQL7fCnVQiablb5UEEsIBLh7lu+xOmVRmxQ55TLlS1t+EQGTuB3KwmO1qfIBy1tTMsO70yfVJ2YwKVe1G2f08tVUInEfBpLjYD5dlijKPR0mKE3zjSgUJ3maFmQ1kIRSqLQRnfRq3JxNbuZtlJ3mC83mJtNIiG2OwtEnq90SJMv0x2Ooob032m5dYUg5yfeslF/nSubtzHidCoACy6yz4TnN1iuO0yvtbDi2nRdU5AaV5agxTk7ThnRWOo63gxscn4DVwqGvHLqk+QikbGdd8qUp+/CDGxUuxJfa2atCfN3xeNCSWQzq8o539Jrzg7XieslJRs6oet3CVpegFBB5IeiyyTsoQwaX7My0+UxhEjTUOBLaKcjbRUUZTS/MpOztVp3qNnhOo+UQpXUBvPyUWzbicmjH6iY6KYFK/JBC5TexoiuaSqPdddkqpGLnyPZ4cU1pIfplGmszrHQMsNnUJCzNSGue6GHDygFDYT0MwXYN8yIU/o5MKVDFBksq/N4ofdr3Yalqs1i22LdTRctVowGFQrKxlIeopKIg8ytVkMip8fjSl2UXgFC6udXhXdhqDnLUPOcDvMLMVX1WbQtPBmGxAqgPB2HVPZc+jJgaqXBHTPlbrEXICdtdrh6Y2N+PXkeNeHp5bHW9nj0DB9brFOtrMdXX7e1p013SGcMTtUUJ6sG9ZBTCiUpBg122WeRvotCcKqe59xqlamVRiassu363Doffj8qxaoNeb/ZFSVgGQaGSu7tasPheK3Qa0YAXc5jugYV16TtKa5o3hZ2WbHLnkYpyenlBvW2i1A6vzDqw1ZwvyJo7/r6KR6jDvHk9X+FR7wUpm+G5aN8YPJNrKgx/uezrr7QXRygA3vHS/zbK3+Cn3/oPp41cz03jT2L55z6Q/7soWu81HgbR/29qH/5VbjpL7e86AcYYIAB/tuhtCG52vKp2V5sTCqMRIQhORjbC3rWmIp21aOws3TkVNMXXLJ+S+b4hbaZ+bvTgkxfIuupCuW6g+xuuVLQDAR+SMxEWPx6eP0ovtKFsdccAzsQNP3EpBBKxt6EgltmxFsPRxr2Q0rGaidZqCVG0rbQyHP9JEcKYKGpjaykT8kgRsOcJgBTBex2zsbX2ebrsLPx+gksv65ltaWX/akQAoHEDyQSIz63H0peGUO6DLmr4bF6d15kJjNBFEZX97PmVt5vhHOzjhEa25Eq5nBjhivW/pNSS9cqa3kB640meeVgBwbL5RrSt7OexLSLhzD1Uel100m6pxaWWazZeL6KSeBIczabw6RUTMBUH1W8NDp/ftdtwVfOp9ZiipSBJrqODyJwaNeTUMnZcpvvnl1HKIntBrTdIFN7LpFuD/OXwiHreyc5Vc9TDslOetyG9LCkg9FaS615/TAJiO9BNI5S41zXGCf9JfY0jnG21d9oj/PgpEPBXmGPPYUlHWbDosRr9RZnlmoooNwOMKQbb2z02hwBGZeKaAeCUmuOXfWjiEg8Y/0seb+mxTnCMVjSpmAvsq18WNcSS/cvzPXr/KqZb5n0XfmrJ7jrlv/ga9/+Nv76bNfHD2gfYcLX92LOKVH1TGwvwPa0QE8s2NJaQ7RTxdmVwg4E5+pa/EYoxcl6gYaXXicSJWUqn1LghmMf99e0V9W34+8aKyRYDTdgwTZxA2jMHcvUMqs60SutBGu7Ab7T4txag8lzX+s9B51Qiqbtp+Ys/cUaejKVouX64fdVMqYRP71R0x/3G4I2tdLga98/zHuK70fsuAIufzrc+jcsX/Vr3HB6P6/6yQewb3Igq/+jiGLO5J3XP4Q/eOY1vHjlhXyh8EwefuRt/P2DT/A/xv6MLwSPha+9FT7zW11FNQcYYIABLgTOrtaZq9gx0VgLw6961sEJwxaj3foIpaDOsfkqDdsnzrdJ1V063+4hZpUOserRr7QfSheAjgx7xXBrjrHKsR5npc6XukC0QHKmked8y8KRhq5DlYoGa3sBraXTPa+vEORbi0CqMDE6tEtJxXrTyZxRs31cXyJQ7HJm2ebMxcZsJaWcOOYtMx7WREuHzzU8QcFZx5I2pnRSJpVACYElXfY0j8c1zFQ/QxXt4aF6jp3tJC/FCxRL1VaHx6m7jUCqnjLvaa9cICW5kLxpwqaPN2o6V9CRgkPn1lmuOSn1yrAdFFJJpJGj7QWxp2mocR4jcMhJm4esfJ5c5SwSE19KzMCB1JoCTQTO1g1UkBSsjj6ttj0WUgqTgZS4fjeBMwhDHMM1cXDxPzDD8MTJ9jRSSb67VmKxbVF0tfckMsSbtsP8+Wnmq20Wqu2wgHk3jDCkNJCKbe5CTOmjfMGiTHLPHlT5Ng+qfAuzlpKqD9d+lFeU2vvoul5EMgzl0w7Sz2n2yEhQwlA+ly98liG/TKXl4qZUVfNuBTsQWNJmqD0fe2EtZaeKvIftSY9K22XVMWOSt7d1AoGi6Kwzas9zVfUmLBnmEoZjGmpqcq9LOjhYvp6LUT+7UZJG9Ey5fhB7/RXA8nHcQGrxH+mS86oYsrdcfKBgvm1ydL7GztoxRprnWKzpMZnLx6C1Fl5DElXyk26LscoxXD9ACTMmj3m3jOW3OFdusdZw8KVEKcn5sM7ahB8+62EI6Ki/zk5Pb/K0fa1eO103qJ69g6vrWip/tW6z3gzDcAXMr65TWZyiPnsYd/4wzurZzHgs6ZBkmqXmSkmGG9Px5kH0NZpXTrwpk2wkKWw3+Z6KNpE2w/2GoL3zP+7hnbn3MUILnvEO+NxrUTsfxCuXnsve8SKv+qkHXuguDrABhBD85k8+gH94yWP4Pfsl/IvxTPbd9Rd87PJv8vGD/5t3es+Huz+G+sBTYe3M5g0OMMAAA/w3wAskLddHoA2/rCg8dCu66XerLkynRCUA9tsn8IMg9IJo2EHWmBZKxQISSiXKcWD0tMJUUgArY5CiFAWvmqmXFV8jc77U9Zsi40No8YNGbmfGA9CwPZba4a52kIR0ShmGv3kBviIjJ28FLYr1bK0nhc6Hyvs1UNorNuHM6/73GF9EdlwpYrIqUKm+haNJEdm97ZNss8+x3t48CqPa9qi1XQIJ7cCg7hvUHQ/X9/E6iEpna56UuE53Ps+YF4VgKhbKzTgcz5WCYn0Wu9Wi5CVeplxjXhfp7kBe6WLYvlECkpw3K2gy1Jpn0jmPIT0q5dV4o8AInORWhiqZs60ci02JHxK09Io4v7yC29b3UynFetNN1YlL5rQQhjOOO/MIFcR18ADy5TNMnznJFc3bYs9izq2y2vSwfRhqL5D3axhR7lOYm9gJ7bVM1CwjEhJJTeyzT1KQLfKyHefGKaXXq/6jU3C/UztUo2FOpI6A7d5C8mFHfpYjs8+3oHfB5mU7edajPLcr1/6TiUZv8bO1jhDIEX+N3OpRJtrnEEqyt3E0tY7I1CUcbp7DiHL3OiYy6m3bS8Kbq22PWhgaq0DPk4JtoWhOwS1Tai/QC23XY7qm29nunGe4mXjcckE2tDv9fbGzPY3tByhhIFAY0iXvVSl4ZUYCXSJCSsVKJKiSaUm3UwrVYs+1krm1paDRbmeOje6yAIrtRUzpcqYehrKG98IMHHJeDVP5nKrnmW7mUi2Aai5z4twCQSvM33MSr1jeTp5n15fYrs/pJe25PN+2cKXoCpXuhfsFQTt0vsK+43/PE8QhxNPfBt96B3g2H3/A27hzweF/PftqhvLW5g0NcMHx01ft4lOvfjzvLfwmH5TPYPT29/APu/6N6qNez8vdN9JYPot6/xPh0L9d6K4OMMAA90MsVG2ajk9eRrW0sj+zCgMps3lpEBWc7RHiSBQuo/9dsK2Mp0ag4vJVXWen3lhom7hSsOQkhZTXGm5MGAWKRo9CzZ2E0graUJvPGFcC8ESeum8w28oRSF2bLB2KGL1adU2mmjlcX1J1TSb9bN6WnoWu/epMK44f9KS5kC6endQ5yoa6uV2tG8rH8bqqY/WEjA9TSXFspa/Rcv1M/a1eGLG6jfVCkHh6hAoyoYCgWKnWMkb+8NohnKBzBhST3hLCrWEqlwl/tWucmXuZEkOIRq29aRp1208UPnXPACjZKwzZ2vuZVrRLjtD/zymXnFfjovoR9jcPozrqU4162TBfTaB0TwpCk4MRFeaLqf5zGsvmK5V4HlPDPNg+xqXto3HbCp0zpHvafb97kf7emyq6hUhNEbQ6asaQ32A52bK7TVM6cYjehlAKS3o4vi72bRCglGC7txCPyfDtsHZc1h8cC+2E7WyUQwe6KDeBj1ABxfQ67fOsZFROVYBYPw12nblyO/a85p11hprnOr5DZPwKVKb+W5oQ67De7LWl0uHNkUetFRhdaz+5Tqp7PT5PVRFhtH6Gg7Yuyu6l7pcCbD25jAY6ZDOueCYE5HQ03mhzhvX5M5RnjnCwfhftejkOAzc3WNMR7hcE7VOf/SRvzP0b3lU/D7V5mLmZ1Z9+O390i8vTrt7NM67dc6G7OMC9wBW7R/nMbz+BL1/0Ot7n/xzW7R/gre0bePrP/QrPcm7gULAfPvWb8JlXg91dGHaAAQYY4L8P+hf+oH2McW+Zrr1eIVhv6R1q2/MpN3W9rt31w+R6GGc52UNBLWVEpFXSVGmywx+QoOabnG3mkjwxpUOZlJRIBJbfZL3ewvaypk07EAkRAWR9Wdc6U9lw8gAzLojteP3Mo43hGCVAkWtljfdI5KDbKMz+3QqyJk1E0PamQoryXpVl26Ig25TCEDgt0iFji7qXqEEaopf3TqmMl0iE3pnOPveKcC2IxMg3kPQyLzOCBkqxaPeu1aoq52KPgy9hvm319DYMyz6KfekjFaw3HV37TkBnoFc6By4W7gj/1p5drQg65i5hec3MuZEh34sgRHcxkvZvuiqT3xhhue7ghMTVDFqxVL+nulvNeTWGmzOZeyuQ9BJCSY9Dv06rW2aPm20kn7myYzNmc77/A0Gg4oWUvkReOfFzOV1TVGePImsL2ZDMiJirrWxH6Lp7teVp9lVv2xJ5TG8omVEYpFPD9SVB4NP2Au0dJWAkpZgahwpihOIqncGm+t+G35FjiybpaXKaOS3sVVwMPHW/lQJJNk9SISh7BlXP6NgoSbUFGH6LYb/KSEjQYi+0SAp1V1purFgKWU/q5a072el25zmmcZ8naLceOspvLf8xrdJF5K57Ptz0F6iHvZjXH7uCnGHwJz9/7SaV6Qf4UcTkcJ6P/MZjmX34m3mL9xLUiS/y/MOv5N0veSKvNv+Y98rnoe76GLz3J+DUVy90dwcYYID7AToNnr326TjnI8K4vxbv+tdtn0rLI5AKO4Bxv1NtECbc0MOUNhZSio15I7lw53543fH6WmFCKW14h31pVFYwpU2//KvIYHL8gItb97DPzooPyNTvqN0jJ6l3o8lLVxRikY50SGSa7HWSnU0NzKh48wZH5rwGhvIZac7GYXAbecE6AkPjfph0KGD2tc673zdSUuyG6kHQ1BbGHa8Bg3yobLnSFilxkigMsNV1aj867Qa6ZtVSLSt5rl8mnlvQ4ZuIMA9OmAgkhgowlGSkORvmSCUYDiqAwhTZ0VhBK+5POxC0A8GR9WR+hsx0b2VMXIvuelzIvBdyfgOBotNJbPnZEgy9yHk6bzToIH9SKk7U8yy0zS6yWetBJjbDRms11SOG/KxHslOEJlIGXcjy4hjVcDOl4QvKqVvjpaRYW47PasOhGTo3S1sg9VriX2Y3lnwbkFjKDb1+GhNeUrA5Uk9UwgjvkUraS6HiJREAPwxE5R0AxtxlXf7Dtli0LfY4073OQCmott3MJkf83auijYUAz26mxhB0ra1i0P0spnGfJmi+02bss7/OmGhTfO5fwud/B3Zdw6f2vI6bTq/ye8+4ij3jxQvdzQF+QOQtgz993oM5+Mzf5TXe7+LPH+Lqf38On3nRPr5x8St5rvNWlt08fPT58Onfgtb65o0OMMAAA/wXIDrk7q0gawAWZHfR17lyi2W7tzEXqR/OFS+P3zOd5LtsQlVQQN3Vxk26H4FUfQlXzquAkrTD5HVXig1CubIYShkmkecksxPdAz3FUVKQwqQkmx21wrJkb799IiloTO/cnuw1NzJxRNwv0UO4YyNs81cynEkqRU46fQy6e4dLnFNdO/daRCOFDVwzO7x5hgNtvEf3fsJficlLJ1Fq+4K1YLhns1LBiXqe1dCD2tmv3iGOmiQaSPzASwpSkeSG5dxEya/XskiHk822cpmOjeR+MO9s0na6v1LnNoZw/CRzK5urmfQno1SaarfmmwjxwyENm8FQAeNed0mHzDF9aHevumRR/hWAmwrZbIYKhHMtA7nFbweBYq87zcPn/5l0eKXlt7E2KNBsKJ9ItAeVbByN+JW4XRWGFqN0eYyN0N8LnnxQtJcTL18P7/lYkH3uIs9sJNbSq1UFCKHIuzVK9lLcdyPwkpp6IfrViItwnyZoUx95DVcH93DiUX9C/sY/Bhmw9Iy/461fmuLRByf5lUfvv9BdHOC/CCEEL3v8pbzsN17Lq8230qiuM/GRp/DRxy/z8Mc9lSdU3sonhl+IOvSv8NcPh+/9vS6wOcAAAwzww4Yi9l5oiExdnV4otef7kqg0ApEOxUle5kKFu5W23qeNdqjzHTvsncj7DQrOKpVWEqrY6cGrWkld0M129oNNzAmhFLbX/7t3M4IHYcCg1Vtt2c5v7z5+A1IYfSLUVr0WnX3JYkjWGZKJ0bhZeJsTCnl0tmopb9P+eFL1JDagZcZHg3JXJ/NBm/Hq8a7jz7dztK1xFAJDqExuVC1culq2XmQM9KiYeWDkUu/pfwNhIpRkrdYiCJKwz6g7Ba+S6Zy1CbFJy+z3Ovbe3L+NfJF6Q0M/Q01Hhx/r97a2cfFfNagNleSuboaYaPcZutFHhCLK09Pnbm7JYVgAACAASURBVG3efF921QzrB6EkY/66FuaJC6qHxJyttKFDAqJ7usfVokE6M02/Z8r2pt9vld4ik5kxpz31Kv7oB4+oS9ZJtwhIL+9u/0y56PP7KJo3/z1XnP8knx2+noe0boWlI8hf/Ade/9UGUir+/JcekgkrGODHG4++dJIbXv9y/tee93LU3UPuEy/m982P8n+ufzhvqT+X63k75dEr4Ytvgvc/Ac7ceKG7PMAAA9zHoDd400aPwC7s6HO0hindrRlKqWPSP+siEnUUsNrcgsBAtlGMjOBI56dbh9yCOZE28lwpsjXZOo4t5fsQtj4/236um7iJHrlIo10iHVuhx91wOsI4I69VhH5hntEs+fQXJtPGdX/7pNr2tBjBJvBTE5zr4bmN4CqTmdKDaAUGMymRiyPL0RgUBWctI62e5JylxxF6IYQZK2dGXgT9qe6zTCmMSgWbmWJCJde1wmNLspkIYmzRlNM5ccnBxR5kr+0rvjPns9Tw8aNaY1s0lTvDH38Q3NvNgn5H9yNoaXhS4fVQbe2Eu0UPsy9ymdxUI3Cx3YBWWMNwsxy2tdxe2tZo6GkNcwvje6RCISUopDyw/VD10t8fyX3p9CDHSKnS/leg0Eq76UgKgSLvdNc+20wo5L5J0M5+i8LXfp9vyIfyuGsegDj6KXjqW/jg8mV8Z2qNP/q5q9m/fVDz7L6GXaNF3vWKZ/PtJ3yYjwRPo/C9v+Gnbn05n3/JA2hOXMXDZl/LJy77M5TXho88D/75BQNJ/gEGGOCHjI5deaN/UdsIC2LXhp9LYeKl21F05e6crwfcdn7jnIZOCMSGYTadnoONjMfNPGh+ysgL0IIl62np8A7CUTB7iAEgGCv2FsfoiR4G+GQhNFzjy6k+YgD/veicy8Cw4qVjIPsS3uSedI5NdZ2TrpNW2CDfpSpGenqJFIq2MRz3t+gk4i2VnBZXS+fwRJCY5JRLcQNSGPU/UCJTI6wXcqkw4WiZFGULKySMWydoZKbtsm3dc3x82aEdiKzQSB8y7EtJOxUzmRbT2Qhb+U7YKjrDTCNMeoubnltt6xprm0FuppoTovM5yvs1XQ8x7GOv8O401nN7wrBkhRnWtE0rcnbW/dsqtkp5w32uvsgZm0QJpL3CKSJoqCApc5DCZoT1vkfQlo4SfOxXOBPsYfnS57Hze2+Ha3+Rk5e9nLd/+R6e+qBdXP/IfRe6lwP8N8EyDV779Gt5yCs/wA3F38VYOszFH/1JPvrwE/zaYw/wpiP7+UXjL1l5zO/D9Lfhbx4Nn3sdVDZW0xlggAEG2ArSP9I5y2D76OZ5zr6Rxxe5PmF+invGHp8VaEibHEIbFk3H70s0fDPZkByxJPuHQsNAqQ132tOeA4XgslGPfiaMv1VhEHrnhqUJwlgxRz9bqL8xfu/C0IwUz9ksDDXCD0OVLwmCyjZmug3WLU3ULeX2NOggCXVN5+rl/IYmdWbvtVa0TPY6ZzLeUtClEU6XrqNhjPfoZ8rb1QPr+ZCgpUJvnbyuFybD+xsJ5JTM7Fg3ynbsPBayeUHp3kyGeVibGbLR+hci633uFXbW6KEWuVGIY9O99ykTa8OX3utz+sHv490y+6yfHwRb5Geb5pluRpWkMInuptWDzG0lDDqNmrkN0KUr5Ib5qOAEEsfvXW8vQrGwhc0hlYR0Roie5a1EGWTPuy+hOof66C9R9fO813ghvzT/dth7HY2f/St+66N3MFa0uOEXrhuoNt4PcN0lE/zuG/8XH7ruo9zuP4BtX38jvz33Zt733H1MVwMef9ND+dAjPoV8xMvgrn/W+WlffDPUN991GmCAAQbYChSCvJXLCFv0g8RAGt0GwLy1j/HqsUxdoDTSYttebgTXGtnwOiOWTIxgQZfRnm08+1tpkE1sd3JJAV9XKhYK/Q1Pq5j0q5ehkiaRObP3b7SBImf1Nlu8Hl6JXq1YRqhmGDNAheU1sY3No2o6jTdf3AtvXgTDYCm/L1sDSgXk3TJBuE5ysrdXQwBiI0NzEwbZmWMoUARhKYKupuKDet+L9ZZej9LI4VpjtEoXxWQtCt9MQhAVvjlEzkxUNfsV6o03D9J9SY0rPW9DW1AVBOLnzxDZezjanOm+Vo/zt5qDpvvX/9jAyHF6x1M5V/3heWwdkSXle4o+BeveEZmV+sZ5b+uFi7bUTtsY7fuZ9r5uvD4VRtfmTb8zdgz3XrcA9ZCYRc+TgYyLmPdCYOTj8OtOcpWGZ278HZETit27dna9b4Xf3fdmHcF9iaDZVfjoL+E3K7zZfgnvyP09YmQX6lc+zu9/7jRnV5u8+4UPY+foD8+1PMCPNoo5k9f+4lMYf+UX+NuR1zCyfDtP+fKT+fBl3+QpV2zjrf+5yi9MP4/pX/02POQF8P0PwLseCl/5n9BY2fwCAwwwwAAbQRgIA6ojD9z0UCUMgg4PiC9yeCoytrI/7lG+S9YgFLiFHV1GYtroiciZAHyjgEF/71GnqdIcvoRc2mpI1z1GULO6hTri/pqlzLFdn6fIqaCfP0xh9nGhrRYOdL3XST7L1k7aw/u4fNTl6gk/vJZCGWZszG2ETuNtK+d0ol3aQyW3O/NesTUfKtjpye1HPCxDsTvXP0xM9PGaRBwr8qoYqTtrF7oNSo3sWCOjN4KMtwYEbmEyrDmnQ1BdI7uOpdKbBxOl1D3eQo4UwGL+QCaML7r9aZJfzW8SImxqu0+QvYc7yndtqQ8KEYuTVKyNc0o3bsfsuZGwVXiim5Ss5bdGnv4rWNkkBDvCcr5/dNpi/gAFsz/lUAgQIuOR7XVUjA0cLcmmQ6p+3YZ0Z2vESeQ1QZN9NmacwjaCoX7PU3fkQGl4bMPr3TcImtuCf/lV1OoJ/sD/DW4ofZR8zoIXfYoPHWrx74cWeNPPXMnjHviDP1gD/Pjimou38ZtveBs3PuXzfM14HNee+GtumL6etzxokenVBk/7x7PckHs1zVfcClf/PNzyHvirB8OXfh+qc5tfYIABBhggRJp8qDDLa2snKhCC4XzW6LeCZthWH3Q0P1KwGB/KGhDRuQ8cccmHHqRLSh5DpuTSof67551ESgmTXYXEk7dSOBjv1m8saQ/KsOI2PUvnNfmhkqHOc9o85yf8kF4G1Wa70+3CTjyjhFPcAcJkomRlomkkRpxvBXCueMWG7UG392IrMEVErFN3VAYgRGxEDqveJEyq3qZkZegA1Q3IcVc7qVZaw5fQKl286TndqpNhGx33vZAz8XsQCUID3AzHLZRk2NpIUzF8Txj4KcIX3bJo/saKObZNbkwg/HC9BQqqbvr5TBBgMl94QOa86F4pYfDAEb2RsZbrT4j8jjlay+3NkCo/N9rzOSkYvZ/u0aIVex11fzdf9xs9BVafuGHfKGbmuBOdIiG5PkQrEGZmnZwaemj8umrtiFULh7uEehIC1Tk/UqU8oCnv/UaRcIGRZ1spnwm5TOd7dZK16PsojabZTZ5E+B2WK2bvczkMTXbzehMjb3Tng4K+V5P5VF7oJp7OH3+C5rbgn69HzdzMh7e9hpfzabYbdcSvfpzvVCZ42xeO89QH7eZVP7n5DuYA910YhuDnfvIxPPl/fJpPP+qjnFYX87Kzb+CTvIknTyzxt9+c4qf/cZbPXPpHqNd8D679Bfje38G7H6rr562fvdBDGGCAAX7MoDC4as/Gu6QRCspGIRgqdKviGQgKlsmuiw7EoYAls9vIEQJ2jhUwBDQz4UYGE6VcrIAHMGQpri6VGTG3loMm0ARt2FJcOapD8DyRiw3CYNM6aAbDlmRvyadd2oNrjeHnhljP7WG29CAi07JtDOObpQ0NzXubpCCFRWANx3kozeED5EzBjpFCbOj7Isd6KHwR/b0RytYulgsbl+rJGQbbh/PsGM4zlDcxDRETDDtFBrUQp+C6bQHjuYCRgsDsYUyHHL4LQXGS5fx+sh6D5H6cH37whv1UQjBsSkZCw3l7fgverRR5idsJr+91zZ1g4qIH4uTG2VvSBH91/Noe+YT6jStGkxDPiyZKpMdlpI4cK+Yo5Ey9IQ80hg/gWr3D7KSwCJSI1TcFKvM8BMLquufjQzmEEOwcLek6feYmip9CMF5Knt+mOcZi/gA502Bycge+NdyTZO3rEdYZN7nBajcN0ZMI7Bv2uWgk/T2SDoROkAuJoTTy2KU9mc/s/GT8urPPY0WrS6xnJXcxSpgoBKMFi7XcHtYnHoJtDOGKAohkJBeXfC4fzYbxSmGCUl0eNKWAXmHYVn9COVEAyzIy/V7JX4xjlDg19DCaZpJz2S7uxs8l39Fq51WcHHp4t+BOcTeGFYXuZuEaRRbziQf/wLC+n0MdSrQKwURcx0+ghjd2Gv14EzS3BR/7ZZi5mcMP/gMeu/JJLjOXMF7wUU5al/OKj9zGwR3D/MX1A0n9ATSKOZPnPevZPOj3v8UXH/63LIvt/G3z9fxL/k8Ydxd4/b/exfM/scp3r/sTeN0d8LAXhTlqj4BPvwpWTl7oIQwwwAA/wkjv8iohGC5ajBS6f2q7DIDcNiaHs0bHA4a1EXPJZIlH7Mmh8iO4OW2A7imG4Wqpn7ZIQtw1RzJ5b3smhsjtTjxCdlEbBpbfwiDIhBemd9I7k/698Np5y8QRRdaK+4nUPPrlMiVtWVxS8hnLSVaLl+IWJtEZbVnjsW2OMZITCMPYuveR3gqT0rBwrRHs4u5M/93CeLwDH2AyNfQQlvP7aZhJTt1mggQr+UviY/yO3JRILGO4YGEYBsIwGC7kmBwuMFrQ5yzls+ROIdgzlmNPMUCJHNtKVpc3VRgG5VJiCI4Vc9TDPnd5O1Pqir7Z+96kvRYjVsDFJZ8rRt2eHo7+HsrUOhaCIUtlPHSgjWx79CDVA0/HGb9U51tKRaO4h15In20aRh+PqqKQM+P2kzO7jx0tWrSGtJfwvK+N853FgLyhYmPaNke7xmgaBjtGCli5HE5xJ6ViPtOXnYVuIpuzzKyHSQgMIeLQ3F6S/abQfQQojO2MvdwAMp8Qzu57ILrmJjDyXDxqsWPIoDA8Ho4DisUhtg9ZGQ+ON7Qr7mMnrMJQ7EHsnFNBd55oJZeE9hmGID++F2nmmSlexdnSNQCsDF3G0sRDdWup75zxUg5f6NDPToI2klqL24ZS67jQP9/NsPJcNymzCpDGKNOla7hy3OeKUYcDwx41azJzPdMQ+PufiBJGZsR2YTuBWaJV2heOv9PzK2jlJhkPSWtUyW2o4/lVwoiLmTv5ceihgJoZx4af/ijDbcHHXgDTN1F70v9m4tAH2G+sIn714yzvfBwv++D3KeZMPvSyRzFe+gESeQe4T2O4mOOZz3kBj/rDG/nmUz5Ha/gSPqPeyJ9Zf8fM7DS//He38mv/cpZDD30L/M7d8JhXwtHPaNXHj78UFo9c6CEMMMAAW4QQ4tVCiLNCCFsIcbsQ4okbHPsLQoivCCFWhBB1IcR3hRDP2eq1olydnKE4OKk9QXtSSo4jBYtcaRTDzP547x8vIDq8JmZBC2sI4NH7hnjovglkmMuVNxQFQ2VIzLUHdrNzpMADOkT51ieuy/zdGt4XCpIoDKXJk0B0EY2usENh4BS2MTmsvU3SLOCMded+9UJE9qrjV9IoXYQ3eUVYKSvxiZRyJnvHi3gFTTomhrb+2x0Iq4dAis7Jk0aOiaEc+/dfxtLuJ1GZuCauIyaFiWvoHf6DO0bYHooPbKRId2roYSiR7NBHpBk0sfNyE1pqPhI0MZJ7baG4aszlkdudTJsKAzP0RtkjFyMMg3zOoFXcGx9jCMGlBw7GfztjB5kvXhaen+3v+dKVffu/kD8YjjHWtOTyXXoM0ixQMhWXlDzc4b1xqFc63y5WeBRWRthmx3COq7epLlEchQ5pVPkxLtk+joEkL3y2Te5gRyHoKaIznLcYL+YyBvRi8TLaJU0qsiGdydhLue62to/kObBdeywXC5dSNydi+h3kRjk1+dPcs/fn2D3c22CO+mBImZnnzlIX0XxOhERCpfUqRfaY+Jzwg2g9loaGM6QkIqEAu4oBaykvb9STvcUk7Hhyz0GGxkOyJAxKpsIt7WJ096UULcHOQsCVoy479l3J+q4nZPqU3jSaHM4zORLmy3U8C8IwGMmLjvBLA0Po8V46KrFyubgPRtj+2PgEOy+9jur4VdRHLwubFuwoGUkoaOpaBordpYDt23diGQaWaTBWzNHYfi0r+57OuqU3XlwrG6XglHaS330FDCekMXqetxckRVNSNBSXbh+Kw8GbpYuZ2v4kVGkbudJ4hsgOh4m3jdH9nBh6BJ1QhTEuuuJh7BzT89UYOQjAwuSjOH/1K7Hzk4znAi4f9Tu8xhtvQP14ErTGMvzTs+Hst5BPeSvut/+aCVVj5Xn/SmPv43jZh75PueXywZc+iku2DeqdDdAflmnwpCc+iSf/3idYfMUhRi5/Au/Kv48/tP4vR2aWeM57bual7/sqd2x7BrzuTnjC6+HU1+D9j4ePvRDO336hhzDAAANsACHELwPvAv4UeBhwC/AlIUS/+LQnATcCzwqP/yLw6Y1IXYQgNxIbtAfGDLYN5RECVIp45S2D4WKxS3Evl7fI50ykMDkx/EimStfSGDnAA7eXMAwDjFycQ+KHJE2S2DOuNcKVe8Y4sH2YvUOKaycSAiBGJrGL2TydiKB5hXFQCtco4uVGM7vDneLocxc/g7OXvhC582r2XnIpuyYnt1QwOTofIDCHeci+CS4az4eiAGFYXH5Ue7UMi8aQ3qm2UgZg1K+cIbhq3EWgYk/PUn4f5fzFuIUdNIYP9ry6ZQrylsDPjaCMPIwkQh1ReQJBYihvJCoQGdVRBJM0S7RKF+HkJ2kN6Ryl1vDF1CauYWXsGsq7f4J2FDImYEchoNDBBXYUg9gbOTpU4uCI7FmYqeIYmMOTjBVz+KHgxLApSSqWa9Ryu2iGuWVpEu/kJ2MRj2iMXn4MU8D2kUJ8wWFLYY3upGztYjF/gKq1g7FijlLeZCwM4/OsEYop1Rhr8iCM6WuWrV1cFIYztq0x3NwI0sgxXDDZVfS5bNTV18wHocBIFjnTIJ8z2T+SjOmqXQXaQxdzYviRuLseEt8HSSLcMDmSY1uHwp8QIhNFZSBjT4Y0S6wOX6Y9vCOKgmWybXwcdl8bHx8RGK1gGq5jkcMf1msonXe1PHZt7IWOcuwMAVhD7BwtZDxoedOI13VMeo08XkhCRRjyHOUqWQas5i+JzzcNQYBJPlWaQBgizgtUGFiFIZSwdLcnkxw7YVq0Ry7ByU/ihSF+0XUBHrlvlCFLxflVkFVtJZyJKEwy2iqSGGwr6FmOsCdcB2PDQxhWnsAqEVhFTawUHNy9DS8k+ivFg/H8WYZupVAaQozpjYpCziQ/vB23sJ2x7Xr+F4cuZ7aYbEhIswSlbVx++ZWMFKLc16Q/htJiQwVTUAwJvTJyFC66NnxtxusDYLwYEnSM+DnzrBFA0Bg+QHHX5eRz+fi7wy1sY2/JZ1vRxMoVUMLEFKCK43gF/T2wkt84PDo7gz8uWL4HPvAUWD4OP/0HuN/4Cwy/xc2P/yDjVzyeX/vH73JqqfH/2jvvMEuu6sD/bsVXL7/X7/V7nbun4/TkJGlGM9Ioo0CUDAZkEGDWazDBa1jvLvbCOgGf1wGMBbaBBeRvbWMcFuy1YQ2WRMYSEpKQGEnMKEzOndN7dfePWy92mJ7RTIfx/X1ffd2v6lbVPXUr3HPPuedw7xu3sr5ldm4PjWY+ulvz3PHm97Pj1x+g9xXv411NT3Kn+SA/POPxmr8b4TUf+SJ///Qkxes/CLveDc9/Bz59PXz+FbD/gYuTJEej0Vxs/hPwOSnln0kpn5JSvgs4AvziXIWllO+RUn5ESvkDKeWzUsr/ATwMvOpcJzKMSuLnGTvGVKoHQwhm7DiWkMQsH9MwKNph7KDTVZorNhTvL4eOHohPM5iGllSEl3XALW1FZYXp2EVXNkJDWO1bHTSiaFUGIw0vgUFlMv9URHXqJIIpV1kepDAQUu03Y4YZzm4J3BQlJ+0mxo0YhhB0RGbUvJ5ECwiDGTfNzOY307X1eppTYabtOGNeM5uz8Nr+ijUlEnSMCkaISTcDCFpTHkPJtUBJKVIWtIIZZtJOqTDoonbuyETrHqaNSNmls+Q+1xebIesWKQhbRUUUgoatLweUS5I6p+JskLNrwsuVr0O15mP6gTIrBMRKForK9voR+tKb3hCw31vPiN2Abzg05/M4geUgnwhTiLUwbcUYTw0wFO5g0k5QcObul5Rc+TJRl1w8RKZ7C2ZDJxHXJh6yeT40wLGmvaRCMJHZyGSiiwlHtWVruMCm5BTPeetrjmlYDuOhPFOpnvK6KTtetoaVXDqlMJGGQ6HoM+UqC3A25pILFbkyM8WEmymPBGQ8i4EgoOOMHcNzLCaCeV9DyQFIqHvNDxIOTxkeh0K9YEfwDRs7FCFl+zXRQKvb+0xqAwXLYzBVpDvu0xevRNss7WMIQaKxHRJt4ESQQKF0/7sxqLLIlSwza6vngtZ8qwMFSQgaUimironhRpkOZZiwU4EsNiBwDFmuqzRsDuVvIGr5SCeCJSQJB25e4+HGM7SFi/QlJRvzIcL5XnCjwf1dG6Sk3pVWGAZuMkfaq6wvje8Ug3lXIgg2YZmCxmSC4cQAZy1lLTIFIAyV881wOBHtY7rnZeoAZq1F2jAMnk/soHyvJ9tIRRzCjoVrGfQnJMVYCyCYCDUy49QpaEJUrHdCgCjlMoOQUQzqI7ADZceMpGuiuU67KcYireAlKRpqPuiQk+dYYhMgKBouZ1IbKFphjCqFKeVKIo5F1i2yL7KdU04rE2bFij08qdxWHdMsD2BVu93mo4JQ60aO5fbUuFpGAzfTyXAzGBYzVpQGV+KEQsH1CqydQNHLEGvqVc9qzJkVLCfh+DR6MhiEMgjZFulYGN9wOWk318yDm4/VpaDtfwA+czPMTMK2e/Dv/ygvTkf5eOen2LX7en7uM9/nqSPDfPLureztX1xYUI2mHscy2HvFNt76nt/g1z/wm/zqrWvZGz/Cc34j731hD9f/H4NPPniAw+E+6LoWjj4OX3gFfPpG+Mn/hXkSR2o0mqVFCOEA24Cv1W36GrDrPA4VA84spmAlP49gIjWA0bGTDVfeRFd0hpRTZDy1ljMdt5NobCeZTFM0bIrBJP1k2OaKRp8GV+JGEjQlPGwDQibQvAVMl+0dadb19zPhNTES7QLDoilUIBMJOhoDt0O8lb58jKRnBy57gXthci3HcnuIdW5nMtRIwfLwnSgToSzhzh24trKqtTRmeNHrBwQhQ5LNtxBuGijLaATzagCym2/n2g3d7O3waI5ZNcFCDCRFK8RIqAkEOF27MLO9AAzHexixMwxbDWzLm0yk+hmJrmHcqZ04b5omT6RvYDTShmkY5aS5BctjLNLOIVcFALMtk7UdLZx18hyJrqdgRcknQkz13saL0Q0cyN9KoeSKKCpzdyQCw68K0mCrgBDVXfiD3gBu01rawzPBlSx11CSpeJzjDTvItXaxozNNKnCZCtkmhGLQdgXYHkXD5VRsLWcK6v6YdpK1ud8MCRjEIx7t6QiYDsK0yUQdXNskl20kmu2ka9droO0KRkPNZRmEgJjtM2lGOBDbUQ533pryiMdiNGRyiFAcEDyZup4ZI8RMwwCnnYr7JKk2on17OJm5kgkvTyyYT2Mb0FjlQpf1JHGnlEfPpDsb4cXIen6cuo7qLmXR8MrBTyQGWMqNNGRbNF/xKo7l9mI2byIVcehKKDnGzRjSsBiNdhGyIOWCCMXJJSMkmyuB3gSA9GnJpOjMZ/ERFEvz7CwXGc6UA37sD2/Es00irlV2SRw340gpmHYSnEmsLR93zaa9GPEmZKAInYl2cyI2WJ6jWUytYUPWKM8Rm/TyOD3X0pbL0h2dIRsRWAZs6cozsGknm9oz7OxvwzDNoJ3qgnpI2N/6So40XV/u359ObUIIQdr16Yn7pD0TgbJWjsV6GA/lsb0IAmWBa4kbWE6ofFwB4KXIRUwaknGavQKpcCW0f0vSw810lutT7bp6MrEByzACq5PAdMO4pmQktoaiGSafCJHyHLZnVR+nPkm2gSgHv1nXqK6ZaQhawgW6IjP0ZUP0tVWnmBBKQRWCTCKKZ/oM5GOke69kKt7BeLilHP2VSMW1Mx2CGwdzzJMSkYZIkFaheh5r8KwM5OPEm/qZjrQyEW6hsSr11pZ2Zd3yLY+xeC9TboaheB/FUpTH4BgFYbO7L0tvPkHYtTDlzKy5c+nAzdVzLCQGHbHKkE8ppcC5WB0Kmu/DN38P7nu18iltHIDv3csDcgvvT/5P3nzHdbzh00o5+9Td27hhbe7cx9RoFkEy7PDGazfwuf/283zlV1/FnVuaGbUa+Gjh9ew+/G5+ft92vj7arsK0Hn8S/vL1cO+V8NgXoTh3YlmNRrNkZAATOFa3/hgwd4SCOoQQ7wRagfvm2f4fhBAPCSEempiYoCNSoD08gwxGTkm0kohFiLetp6NnHZG+a8jnsgjLxo6qDoEUynriB6mgNzTH2NZX5wITqcy58UIhJsJ5mhIhWqKCuO1XoqrZngpMEHQCDMPg6t4sA/kYthtmKpTFyfczGutiKLmOoqlcoEzLxTBASKUsTNuJcq41ywkznK5EAjQMykEPwo5Ftirq9P7wBg66PUhZsYv8NLZDKR1V+GaI56Kb8YXJrrYQO3tzzESbletlQzcn217G2XAnAFOhLMJ0SMejSKE6rKPRbvI3vpuiHSfiWmxqS+I5JqmB3ZyIKnenlqSHE6qd5tCS9LimV1n05m5wIzCqqO1nrQwTbgbLNPHjzapzLkrzhuBnbtxNfz6G07IRIQSb2pL052MIUQnvXs2pzPZKmwd0RAokbJ9CtAnywXVOtDEc7wMEBsra4VoGQgj29GaJ2/UJtwEkQ3aWXDrNXeviGIYgukUtTgAAIABJREFUFXGwTJNMro3peAeNiTCGl8K0VQcyFrJY35ygc92VuJt/hqHkOibCVYoblY5iJiTJrdkIaaVkn3ZbgrMa+MKqsQ6ZFBiNreGslS1bVQDov41Q3w3cvqOPLV05kmt2MB1Vx5k0whxqvZ2DbXcgY8pVVJg2U40bsZzKTZZPhkD6NKfCZDJZrOZNFM0IuXhlztR+bwPPhLfUyNGQb6cjMsO4l2cmM8BobA3DCXWvCADLATdaSQkhLKYD9z/HMilaHjMNaznq9XLU7aSIRXjgJtLR0hzTijJgOa5S0q2KAmAZouyWGrV8djUL2jt7GE6sLd+N46FK/zVqS6wq10zH9ZgMNzGU2UpbKqzmZNWl/DIMwEtitm1nTXsbpgBhVq6/23UVLS/7FQ433wRUQtifCHWA5ZB2Jb0poPcWyK3DMSvWZs8xWVsJ7lgzFq2UDjht5yk29OOmg4AaQmAIaAkXCIdc+nK1wT0SYRvHtFnbYLIuMaks76bLRHKg5hE1QlVRT5s3AdCUCJXv/5BVGVQpzSurdmstKbBR14JQHL/9KhDq+ejLR+nNRfGqgnqYQVj+0jFH7YrgJ5KbiDgWubhqd7M4hRQmXuDz3BhzSUdKCprJtq6GYD5tlfV0EQ5XK19BO/sC/Pmr4eu/oV5cY8eRL3yfjztv55fF+3nXrdt446e/z4GTY/zpm7Zr5UxzyWhJefze67bw8G++is+9ZQdbOxq4X27lbTP/mU2jf8T7xt/M034L8sTT8Ldvh9/thvs/oiy+Go1m1SGEuBP4XeANUsrn5yojpfxTKeV2KeV2z/OIWMUgGbSgrUopaWxZQzSVY1tHisaYy6mG7YCgsSHDunxEuRyaauQ6ZJu4zhwJbas6wBOhHI5l0h4TDMd7MRdIApuJumT6dtLQ2sdkKEvEMSl9/pMhoTrQotTZl1hCMuHlVPAMlMsgQtQoA80JD9cy6cjUKkC+sJg2PNbEJDmvwIwIqTkYpc5SVcekaIWZdBsQTZtJepV5QzLWxFS6j7HcDmjezKa2FIM3vgkSrRSCACJmcZyQY9KaDtMYC7G5Va23TaPs2tmZiXBVl+pYlSKq2aaB59g117IUEKA1EihfgcI807SV8Vg3vbkYa9ZuYSrUSKh1PXvbXaKuRXfKwnY9btvQxI6BLthwF4mu7WxsTdLZEKtxCYsFClUl4ERlAC9iS4SUFEIN0BhYdJwIvb0q+p1pSAZTPld3qs5tOuJwXYvqHbemvLL7Xkkp39gSJhOtm9cllJtXaypMx0BFcUl6Dq/d0Vaeq3PTujwbW5LQuI7jQRCJUGCqEIYJtodwVMf0cHiAkearmQ4sgdXzfIatNMl4gmEnX1aClFxhKAXIkRJhh9jUkWVdWrI+rlxNpeHUuuMFvdnuTJTexiiOaSrtIGjDrd1NyjUvmK8lhCDn+fjCZENiqmK5cKK0hQv0dbRxvOVmDrXezlTJFVag8tFBTdCS/oTPlY0+XdmIsrYIgxk7xhmniaKUxEIWazbs5mDr7UzXuQAGF63879rmOLlkjETYosUrlMOwSyEQsSYmQrmq/F5qdlpTrFKXUOsGtnWkMJs3Ve4ToKOtAx8TH6MmCbkfyGNUBalBGGBaXLu2lVw8xLCd5VBkLce8bqQUrIlL4jbgRkAYdDUoF1IpBJNulkTVa0kiGYt28nDjneVLiBD4bhwnpp67UJWZy60L4NKVjShFxjBZkzCC9yZs7Ujhm1aNcrq7L0cmnQYvhYgoD7mWZDiYDykRAg54G2jMV+bodTRUggbVR89sb4hwZVcDDVGXTa0pNrelat5vx5PqGZFS4nZdxYHYNrDDrE/MkGnM18yPnXIbiEdCdVFXRTmKpG2XFHj/nPkiq5kd7malUJyBhz4L//Ib4M8oy9mRRyl07OHdI2/iX47H+OUbu3nPXz5KxDX54i/s1HPONEvG3v5G9vY3Ml0o8uffe4H//YMX+Jvje/hScQ8Rxnmv82VeP/E1ovd/GB78Xei4Gq7/NeXuotFoloqTQBGoH7nLAUcX2lEIcRfwBeBNUsqvLPaEQqpcSQ2REKnqsPlVnaT2dJhHvRyHOl/NxuQUB6cjtDsjZIbCMBoUmic0eonTme20HPxHEILetmasbA/MDM2/gxOmef0erhmbJhVxeBqBgWR9U5QzoxNMWQZXdqU5MrmPMaGsBxNmjKO5axhKDgKwuT3JQ8+dJmSrUOIvWz/bCNmWdJmcgkzYJOV57A9vhznyLm9uS/Lw82cYj7QjYo34YyMQStZ0zPv7+th3dAQLiCcbyOy8m9iZJxCPPs6QLNZEkWtvCDM0rka9exujRGQHRiRFe0OELe3JskumBNW/8IvgxnBGTjCYmMaIZtl69a089NUvlC0+O1oj/OC4CUiy3Vs4+swPcQzoS/r0pW1K04TmSjgbae6vcYrdfdVVOF6ML//4pKqHMGiOSPypIpRyQJl2ZU6MEMQTSR7L7SFiPMKmhITq3FMl98ZYI7KnH47+HZYh6G5OkHCH8QUMJQZIDP2EiGsT7rqKqP0c40F9SzHq7OpkYASKrGWAFWWmqPpUbakwz44LZEalahCypGwaFLwMcAhDiPK8SoBxM0nu6ts49Y1nCduzrw+V1sAyDJp7NnPkZFW5Uu6rWJ6umTHixVjZSrwx7TOVClOySIQduxzxc20+xuTwFNbwDD2xGXLxENkgGuFgU5Injw4zkpidhFwA+AX6GmOMTfucOAOEGxjInIHpaRgzaIl7nLFCrOuO8E9HLMJOYLXJ9HCmwcM3XaDuGSxUgvUkPYe3bFlD8fEsxkFlEdzb38iZo+OcPB4lnUmyvj9HYSbM4WI3OW8E23FVQBkfFdhmaFIpyXYQlh6D7IYbGX5yjNCkjdm5GyZV3taSO7BhWhSsKDAB6S5AhbbvykR44fQYRb8bOTxFU9KrPKtBGHt1fwieSN3I3q3NsP80TI0wmliPLDzMjB1j2kgTGXux7E4ogXQiyUB+itDRqns2cB0d3HQl1sl9PHbobKmCKBucGrRoSXk0r9lI+Jn9hG2TdNTByq+jEN7E4cOn6a9S3KKuhfCjNITOUPBsUl2dpGPNMPkk0ViVwlwfiVKY5BO1aROqAx4JL8Ez8SsZjE2wvr+fWK7A08dGuO6ONzCFhbPvEACHWm4FYRCri8qLMOmKSSYzUfLptfDEYxS9BhhR+0U9e96E3+XLteDW5cAvwmN/Bd/4bRg+qF5W/gxEGpm89Q/5uW+mePjIWXb3pvnoP+9jXXOcT795O02J+iz3Gs2lx7FM3rq7i7fu7mJiusD/+s5z/PVDL/LbJ3+W3+Z1XGc8yvvtv2bwwAPITz+A8FKw6bVw1Tsg1bnc1ddoLmuklNNCiIeBm4C/rtp0E/A38+0nhHgt8HngzVLKLy32fJ4pSSRSnD19ADuWqe0UlH1aBEIIrh9oxJdBRwlgBBgxK/s09MLksPpdUu7CVf5FVURcC/L9s3MDRbLK5bGKUoS7jW0pXDmJhc/61jSRvizhfS7JxhAzLUleKKQZL+zhRMjmmt4sR4YmaUl6tGxuWfAapD2LkZZNyNHjKgn29Nyd81TEYW2TCkQiAF9KyKqOc+lKNcU9nj42WnaX7MxEoBiF5m5SrVcyVpff1AlG6x3LYMc1t0Mwv2RWpMlEK3TuhqFH4eQJANY2p8AO0ZHLcOTUEM1uQVkSAqqVMNl1DZFD31E//LpcWLEcHIWZaDOcqWwTsTyYBtIY5nR6M9NOmp5TD+PIIhPdt3N43CKX7AFxODiJsgoU7BhFOw74tYEIuq+H0SMQSigFr3TlhIFtwIwQjMa6GY1188rBHJCDVCfPHB8h6lqMBfOxurP1qQlqOZa7hrXNKTrSBWZSNrjHMZIdnH2xkhN0c1uSzW1JumI+PPNYVV1Kc+TONd9GYHlxNm/o5oFhk4mZIqJ5K4xkwEvTmizCmK2Ui3gLXcVpFSDkJ8+VjzBjx7FnhrFMo2wNBKVclgi7FlvbUxyRgnwixMR0kWPDk/Q0RpXy54SJezbxxiY4czxQEisWLdMw2NSWgucFb94Y4WERpiWpnq+EZ8PZOURr3kL24MFygmzHMsG2oHkj+DMkPJtEeyejR1o46vSSiYUgHiLsZIm5ORg5zJaczUEaiKYjHBmaJBt1Kfqp0lVWCo5Q7tEYBkQyEEoyIZoYHnsK13E5ltvDhAPrmisWpoaIQ1PC49iw8vIpJfwuv6ucKCajgLpejamkitLZtJHxIxYYGQ4XLTgVRHGsTLICK0TELZbdXttS4XIUyXDbJoilSJ/9BtMFX73fhECISvLqtoYIp/fb5OIuDf27IJymKySZLEq6s4FnQqoLMz7BYKoVjo9gT42wZssN6r7z+0H6JCJeOWhIS7WeMMc9KareJ8mww+YrBxnIxRCWSWfGVe8fIFy7EwCDLQnORG5myH+aRv+n0LIVs3kL69MJYDs0dDK1/6fIE4exTIOGRAhRm2ljFitHQbvvVSpC49gJKJn+TQf6Xgbb38rp3C7e8vmHePzgWRpjIR58+iRv39PF+27pn3P0SqNZajzH4h17e3jH3h5GJmf47LcP8LcPR7jt9Ba6xSHebv4jr5n4Fs73/wT5vT9BNKyBbW+BDT8D8aZzn0Cj0VwIvw/cJ4T4AfBt4D8CzcCnAIQQXwCQUr4p+P2zqPlm7wMeFEKUzETTUsrTC53ItU3SqRRmaA8Jb3ZkL9QJAMpBGCrrK/nAADUfpmPn7P3jzdiTwzS7HgOFOJyap/ObaGFmrMiJ5r1zbo57LkxNg18kG4+BY8GavQjLxSlMcefmLk6PTTM2VSAVcWaFLp+PwZTP95woVv/NcOoprFNKSSr23Q5tKXi2YmEouR0KISj6Fdes7kyUR148g+eYrGuO88ShoZr5JMRbgqAXtXiOSVPC48jQBNnYHC6iJQwTcoP05/fjHC8yDVjBPJ3s1ldw04YZJosC+7mvA5VO4+n0ZmIj+zGqQvQj6xS0UAI23EVMSpqGz3BkSJkkqltpItzCru4Mzx/pIn36R9C0meFTPjlhVO4D6Zf7yWXRq+8nLwWhcWYdHBXYozDHJJfB5jiDzXEmZ4o89rRJi+nhzy5WZk9vluGJJK0pjzOFIXpb4hCEXVfWIuhIh3nx9Dj5RAjhWKpeTAA+vlRt0paaZwC9WkAfXMtgb38jp8amcMfiMOmpfmDJmpbsUMpHmcqcrxPZnZjFSeDxYKBipFJszXXq7/5/xXAivHxAzW978OkTSKnmeUVcS+03+EqYHoPHj6u2Ddxdy9c4kgUvidOyiZ1exUKzuydDMZyFs0NKETm9XwX2CafLOdhYs7eiGLhRaL9K/W/aDF51GwNSUhqeiHu2ktuwcDt20N2+kxPlZNcw0XQVx58/SXs4E6wLAlgUJfTtBSBf9Dk4btGTjXJydBppWjWKSWM8xM2Def7ukYPBmrq8fX4BzxJIw8A2AuWvX0WEXDMzziMTWXZ1phh6/ChNxQLDvsfkSJGQY4IdBsYQtsf21nQ5SEyl6QzWZKLgxqHnBjj2Y6aq3wHZCKnGGA0hUU7obBqi1lOudRucVBYpsmupHhRQ+5g0XvFqfnrMhn2PYpqifH3nfDcHbOtIcXVPRs0hnI+StX9Y/UyGHU6NhZl2EjAp1HMQWCsBiGSItIY4fvAZTGyYI/dfPUuvoA0fhkM/hKlhGD0GJ5+FF78Hp55V28MZWHMtbHgtdF0DTphnjo3w1j/+NofOTuBL9Szf97Yr2NObXfhcGs0yEQvZvOeGPt5zQx9D49N89tvPce8jvXz49Bt4vfkN7rG+Sv70fma+9kHMr/06RstW2Pom9XGYZ5Rco9GcP1LKvxJCNAC/BjQBTwC3Vc0pq09I8x9R38Y/DJYSDwB7FzyZrcZWE54D+Y01AQLqs4rNotRhaNqkBibno2MXAtgB0HQHnF4HJ/eV3Yeq63K8cRPMkWNKnU+o7zBAqaMZyajgAAWlVKQjTnmy+2LJheGVG1pANkMkgV80WBf16WvNgGUh57gOyoJW+d3eEKa9QV3L7my01srjBopZvbUw4Iqu2e/PvX2NPH96jAMnx2hPB+Pfhk0sZBO2lQpmW0F3yLQImRYhQDb2wf4nyseZCLcwEW6pHXyvt6CVZBKCK7rS/J9HD5V/V5MK23yn7eWc6biNLjcGDKkAD8VgWN20kVLNZaxMS5pbGS+5lnVGi3Sk3CCf2/z3W8g22doa48gLJj2N81jQGnpq2n9bR6pmc9KzSUcdGqIur6y2qjb00Bd7DmlbSCkZbIqTjbmcGJnDXFBKJBzNw/AhkBLHMpRHlGyAUz9V38OJMzB+arbbb3XIesOiYERVv3HsFBz8ZmXwvhRgp//WmmNUX6HyfCfTVs9Dsl11ssVTpZMF2y3ouXGWKJZpYJU69LYH615dViwq8tZGKC2lJAAV0MJAVCJvJNrg7PMQaVTRoqNZ0r4kG3NZ15zg5OgUM+3XIBvV85DwbJiAmWLlfrRNg53dDYxMzjAfnmOS8GxaUx79TXEYWaOijwI0b6Et/ALtMsP2uvYvPaNSqjptMl2eGTYJu1Ecs6gGmAAaB4F/q0karS5n8L6z1Bw0mjayJVPk9Nh02fWvIeIod+RF0JmJkArP8a7KDsLIKUZi3ch0BHim9vxrX6H+yiKer9qrLR1eWDkD6FX3gPjR4eA5Vc+EkEVirlXj0l4in4qSvOFnOf1vj4EdgslnFzzF0itoz38H/uZtld/RnPogbX8bDNxW4/bl+z4f/scn+cy3DuBLNdnwndf18PZr1pz74mk0K4RE2OGXb+rjl2/q4+z4NJ/51mZe+8O7WDP8A15r3s9NxsMYh3/I6KEn8f7hPykf8i1vhP7bYI5RYo1Gc35IKe8F7p1n296Ffp8X1R/lbN08lyoXxzlxY+p72LhWja4vBjcKTRvUMhcLuZaFMzAUjJxXdyQtp9K5WiwdV6upCNFcxdohBCTbsa0jJCNuOSHsfAw2xTl4Zvzc50q2Kbm9FEwV1HU7RyCmRNhmYzjJxtaqOSlBWzluoETPIbMIq05pS7ZW6TOrrXnnmCtYPlbdb9MQ3Lg2h20amIZguuDTk43CaAZ4BmJ51VcPouCpg9SO+ifDDlMzRewg99q6nEd3k6ey/J0Dy4BXdhYhOYd1a8Nd59y/ez7FzjC5ut3DcKNMBPWet78WiqtznfqpUtCq5Uu2K+XEDimlPNk2+3sYzsDQi7XPXbQR3Bhr257GzvdDoso7xamNqrmuOU6h6NOU8OisC3ZTzod3HkEdSgM0WKHZylk1QkCmf+5thgEDd6j76uzzSuZokOPMEOzqVkre2FQBTAvPVW2/qzvLSfFiTZCQEiVFtTUVnrUtqBC5eEhFIdx6d+VdlWhBJFp4S8dCogiloD8VpikyhZ8dgGjV82Jayh03VBcjouwpVxnECtkmzdX3YySrjDrT534vbGqbI0ALMBOM/NiRFFYsTkVBq/JUKJ0OuHkwX5N8/Vzcsi5X1qkboi57t64jdLwIucE5y4ccixuv3MRXH3vxnMdeegWt+3r4hW+ql2o4DaEEUkomZ3zGpgscPzzMT44O809PHOXBp08wVfCxDMEbr2znl67vKYe11GhWI8mww6/c3M+v3NzP2bFr+fS37uKTjz7FFcNf43Xm/fSJQ/gHHmT4wMNExC9ht26Bda9SI+oN3ec+gUajWZmUJpHP1+GzHOjac1FPubU9iRWaHeodgEwPHP+xGqEWL3HAcwEX7VvW5anWZ3obY/zwhTM1gSOEUCP5nQ0R3MV0jjylODmmAdm1DOQWqdBWE3SgW/u309T7MvDmCDIWyXDHzbdgOLVKjCEEtG5XHcfo4jx56nVlIUQ5mTco90NAJQQffBWYFv7oFAijEn+ublT+2r7Kuddt34ubaoUxlVFChBI1Xn6zaN2urFIXSMSxGJueI5WMG1MW5HCEWCzE+pYE7YEb5LzEW2ByqDxHqUwp+p1pVSUQr6JlKzT0BIrbCMmSBcX2iGx65TllyETdeSN/q0A4QURPw1Lf36ZNCx8wvUZZz+LNtet7bqy1tK6/c+HjlOQeuL0mkXI1zUmPnWsayq68a7p7iI/so6Ftdj/BsQzu2NhcO7BQRcmqbQoxr2X63AhMA8xwvCz/YFOc4ckChFOzi5csYwsNBjVvUUFWUvNriLesWzhbih8oaHdubaGnMab8JxagFCp/sdRPsQo5tnK9PMc+0rA51Hr7guWWXkELp2e5cH39qeP8/BcemlXUMgR3bm3ht165Hs9d+qpqNJeSZMThfbf0875b+hmeuJ3PfnM/v/PI99g0/AC3mj9gQLwIB3/A0ItPUPjnD5OIRrEGblX+2u1XzXaX0Gg0y096zdxWlfZdymK1WOvYRaAtm1p4JD/ZrqwXi0iaeqHUdwrb0mHaAjdD1zKYKvhl97/5RsHnw7EM7tg0f8dzQUq5zCIZjMgcHcgA061YHTJRl5OjU0rhPM8gTyUZd3SmOXhmjrCWNSdV/R1fSjBMjNat0BGtuKLOgZcPLLZ2B7hxDDcJJxYIVJrqfEmBqm5Y2zh3Lic3rtzakspz+FxBSAClkLRsPf9KmHbZffFl6/N1OeFeGuWO/9PBvZXpm6141SPE3GUWaLcFsRcOftdYZbAQXorszrvnLbuYZ+SCnqNyBWbv25tbQNmLNYH5YxUMaT5sD7qvW/C05/Kma015CKHyH547WM3KYtm0nhMjUzx7fJSxqQJPHB5iU2uCAyfHGJ5UuSF+7qoOfnFvd2VERKO5jIl7Nu+9uR9u7mdi+o38zQ8P8ccP/RuNx7/F1fIRdhpPYo2NwMOf5cRDX2JCurhelIaOQaz+W6DtSjWSWB/qVaPRLC3zdTSd8Gy3x0vNQsoZVOZz+XNYQpaAPb1ZTo9Nn7vgArykTuXal5+XC9sVXWkVYfA8OnqOaTBdrGT0bU56tW5cC5CJuHQ0ROjLRVUQl8VgGBBpwFgo+sdFQAgxt14vxJzuXQ0R96W11Tm4ZMHiSvfHKuvcnw+2aVD0i7WBeM6XYvAcW4uMqO6EYfAVF36+RSKEqHXt7LlBzVFcZq5a03BOa92y9ebu33ec93/psfLveMhiZ3cDNw3muW1DvhzdSaP594bnWNx9VQd3X9UB3MX+E6N84gfPcmrf98iffYSN8im2G88QnzoBTx+gsO+fOC6TjBNCOhEiyRzZzrXYnVdDbj2k2uuCFWg0msua7uuhsPC8LEDN1/GSKjreMhBxrRo3vyXnPN+L1UmwF8s1fReuhBqGYPN5WhXL+woV5GWxyuClZnev9vhYqXi2yeRMcW6L6GJp6IUzz5Xdj1csXmpF1HEx07WEPI8W2b59u3zoodmuiBfC8eFJnj0xSsSxyMVD5OLuqjM/ajTLwdD4DP/8xGGe3fcEHPkRzWM/ptN/kXZxnHZxHFtUfN2npMUoHlO4FK0QViiGE8tipFpxMl2EGnsws73K+nYOdwqN5kIQQjwspdy+3PVYCi7mN1Kj0awADv1QhczvufHCXRVXOBPTRfafHGWwKa774UvMQt/HZRu6aoyHavxnNRrN4kiEbV53RQdc0QGoSaZFX/LTE6P8xTNHOHRgHxx/kuTofmLFU6QYIifOki+cJjN6BHvsKaibmiAl+ELgY1IwHAqGx4wVpejGKYbSSC8F4QxGrBErnsdJtRBqaMOOZdWkYnPuicwajUaj0axamjZDbt1l7YWi8g3OESRHs6xoP0KN5jLANAR9uRh9uRjs7gNeXt5W9CVHhiZ46sgwXzp4lmOHX2DyxAGKYyexpodJiVFSYoQ0I2TFEDn/DA0MEZ85RnLihQXz6ZTwEfgYFLAoCitQ8lwKRoiCFaZgRSjaUXwnRtFNlt0MzFAEu7R4MdxQFDccxfGiCCeiwhZbITWvYg4KRZ/xmSJjUwXGp4sUfUnUtVaMW49Go9FoVjGGAcblq5xpVi5aQdNoLnNMQ02SbU2FuWkwDwyUt00XfF48M86BEyqJ6xOnxth/YpTDZyc5NjzJdKFAjHGiTBIVE0SZIG2M02CMkTZGSIpRkoyQkKPEGSXKOJ6cIlScwhUTuIwQoYhFERMfAx9zEQpfPRPSYRKHCVwmcBiXISZwGZNusM5lUjpMYRN3oD8+gzRsfNMF00IYtrLyBYtAIAwBGGqyu2GACP4XojwxvOhDUUqk9PGLEt8v4gO+9PGLPlJKfN/H932KUlIsqrJFX1L0fWSwvlTG94N9fUlRqu3rmuNsa08BojIRvfRXUrtOSrWy5JouZZB3KlgnSutkXVlZV9YPltL/RfU3mldRdqUPvTdD08bzbiuNRqPRaDQvDa2gaTT/jnEsg+5sdM5QyFJKhicKHBtRytrRoUmOj0xxemyas+MzPDMxw9DENEMTM5wdn2FoYoapgj/HWWoxKRJimjBTeGIKjynCTBES04SZxGOKhBgjzjhxMUaMcWJMEBGTRJjEE6p8nFFCxgwOBWxlu8OkiFn0Mc5eiqt1iTgYLCuNSFYraBqNRqPRLAPnFSRECHECeP4CzpMBTl7AfiuNy0UO0LKsRC4XOeDykeVykQOWT5YOKeXisvmucoQQI8C+5a7HReZyegZKaJlWB1qm1YGW6cKZ9/t4XgrahSKEeOhyiOJ1ucgBWpaVyOUiB1w+slwucsDlJctK5XK8xlqm1YGWaXWgZVodrASZLl7adY1Go9FoNBqNRqPRvCS0gqbRaDQajUaj0Wg0K4SlUtD+dInOc6m5XOQALctK5HKRAy4fWS4XOeDykmWlcjleYy3T6kDLtDrQMq0Oll2mJZmDptFoNBqNRqPRaDSac6NdHDUajUaj0Wg0Go1mhaAVNI1Go9FoNBqNRqNZIZy3giaEeIcQ4oAQYlII8bAQYs8CZZuEEP9bCPETIURRCPG5OcrcI4SQcyyh863b+XKesrxGCPE1IcQJIcSIEOL7QohXzFHuTiHEk0KIqeBhopb+AAALKElEQVTvqy+tFBdfjlXUJtcKIb4jhDglhJgI7rP3zVFuydskOO9FlWW52uV85Kjbb7cQoiCEeGKObSu+Ter2m1OW1dAmQoi989RxoK7csrTJ5cCF3lfLgRDivwoh/k0IMRx8B74ihFhfV0YIIT4khDgcvI/uF0KsqyuTEkLcJ4QYCpb7hBDJpZVmNoF8Ugjxiap1q1IeofpQnw/aaTJ4Lq+t2r6q5BJCmEKI36x6Vg4IIX5LCGFVlVnRMgkhrhFCfFkIcSi4z+6p235R6i+E2CCEeCA4xiEhxH8XQoillkkIYQshPiqEeEwIMSaEOCJUv7697hiuEOKPhBAng3JfFkK01pVpD943Y0G5jwshnKWWaY6yfxKUqe9zLa9MUspFL8DrgBng7cBa4I+AUaB9nvKdwMeBe4DvAJ+bo8w9wBiQr17Op14XslyALB8D/gtwBdADfBAoAnuqyuwECsAHgmN+IPh95SqTY7W0yTbgZ4F1QBdwd1Dvdyxnm1xCWZa8Xc5Xjqr9UsB+4KvAE3XbVkWbLFKWFd8mwF5AAoN19TSXu00uh+VC76tlrO9XgbcA64ENwN8BR4F0VZlfBUaAO4NyXwQOA7GqMv8E/Di4d3YG/39lmWW7CjgA/Aj4xGqWB0gG750voL7XXcANwNrVKhfw34DTwMtR/cNXAGeAX18tMgG3Ab8D3AWMA/fUbX/J9QfiwTP5xeAYdwXH/JWllglIAP8P9Z7rD+7FbwJPAlZVuU8Gct4EbAXuBx4l+M4AJvB4sH5rUO4w8EfL0U5V5e4CHgEOAe+r27asMp2vwN8H/qxu3TPAhxex7z8wv4I2eqkepkshS1X5HwC/V/X7r4D/V1fmX4C/WGVyrOY2+dvq670cbXIJZVnydrlQOYK6fxD4ELOVmlXVJueQZcW3CRUFLbPAMZelTS6H5WI868tc/yhqkO7lwW8BHAE+UFXGQ3UQfyH4vTa4p66uKrM7WNe/THIkgJ8C16E6TJ9Y5fL8DvDtBbavOrlQ/cDP1637PPAPq1Em1EDMPRe7TYBfBIYBr6rMr6GUCLGUMs1TZjCo74bgdwKYBt5YVaYN8IFbgt+3Br/bqsrcDUwC8eWQCegIrula4DmqFLSVINOiXRwDk9024Gt1m74G7FrscebBE0I8L4Q4KIT4ByHElpd4vAW5iLLEUKM/JXbOccyvnucxF80llANWYZsEddwFPFC1eknbJKjHpZIFlrBdLlQOIcQ7gBzwW/MUWTVtsghZYBW0ScBDgXvK14UQ19VtW/I2uRy4xN/FpSKGmu5Q+gZ0oSysZZmklBPAg1Rk2onq9Hyn6jjfRlmTl0vuPwW+JKX817r1q1WeVwHfF0L8lRDiuBDiUSHEL1W5ua1Gub4FXCcC92ohxCBwPfB/g+2rUaZqLlb9dwLfDPYt8VWgGWV5XG7iwd/SO2MbYFMr94vAU9TK9FSwvsRXATfYf0kRyq32L4DfklI+NUeRZZfpfOagZVDmvGN164+hbsgLZR/wVuCVwOtRmue3hRC9L+GY5+IlyyKEeCfQCtxXtTr/Uo55AVwqOVZVmwQd4yngIeBeKeWnqjYvdZvApZNlqdvlvOUQQmxAWZvullIW5znuqmiTRcqy4tsENaL7iyiXm9eg6vx1UTtPajna5HLgUn0Xl5KPodx2vhv8LtV7IZnywAkZDBkDBP8fZxnkFkK8HeWy/2tzbF518gSsAd6BcnO8BdVOHwHeGWxfjXJ9FNXXeFIIMYNy7fu8lPLeYPtqlKmai1X/+d7H1edYFoJBqd9DuWQeDFbnUVb4k3XF6+Wul+lksN9yyPQ/gJNSyk/Os33ZZbLOXeTSIqX8LpUPA0KI76A+Fu8C3r1c9VoIIcSdwO8Cr5NSPr/c9blQ5pNjFbbJHpSbzlXAR4UQB6SU951jn5XKvLKs9HYRQrgoV7n3SSkPLHd9XgqLlWWltwmAlHIfSikr8V0hRCfwftRcAs2/U4QQv49yr9q9wCDEikYI0Y9yB9wtpZxZ7vpcRAzgISnlfw1+PxIM/LwT+MT8u61oXge8CXgDSjnbDHws+M59ZllrpjkngdXpz1HzI2cFyVstCCH2oqYnbF7emizM+VjQSlphrm59DjWZ8aIQfCQeAi6lteaCZRFC3IUaAXqTlPIrdZuPXsgxXwKXSo4aVnqbSCkPSCkfl1L+GfD7qLlCJZa6TeDSyVJf9lK3y/nK0YTy5f5fQkU8LAD/HVgX/L45KLca2mSxstSwAttkPr5PbR2Xo00uB5bku3gpEEL8Acrqe72Ucn/VplK9F5LpKJCtcrcj+L+RpZd7J8qS+eOqZ/Va4B3B/6eCcqtFnhJHUIEYqnkKKEXPW23tBGpA+H9KKf8y+M7dh/rOlZTQ1ShTNRer/vO9j6vPsaRUuQRuBG6QUp6q2nwU5UmQqdutXu56mUoeCEst017UN/5I1TujAzUoXrIKLrtMi1bQpJTTwMOoKCXV3EStL+1LIrhRN6JeTpeEC5VFCPFalFJzj5TyS3MU+e75HvOlcAnlqC+/YttkDgyU/2+JJW0TuKSy1HCp2+UC5DiEigq3uWr5FPBs8H9pn9XQJouVpYYV2CbzsZnaOi55m1wOLNV38WIjhPgYFeXsJ3WbD6A6FzdVlQ+hrPvVz3AUpRyV2AlEWHq5/57Zz+pDwF8G/z/N6pKnxLdRUfOq6QNK3i6rrZ0AwqgBjWqKVPqiq1Gmai5W/b8L7BG16VpKEQKfuxQVXwghhI3yKNkIXCelrFc+HkZFsq2WuxU1yFkt01pRG6b+JmAq2H8puRclS/U74zDwB6hIqbASZDrPSCivQ0U1+fmgkh9DTXbsCLZ/AfhC3T4l4R8Evhz8P1i1/YMo/+o1wbbPBhflipcaAeViyoIKgT4DvIfaUNXVoYl3oUJT/xdgADUqNMOlD7N/seVYLW3yLuAOlCWgF3gbKvLRR5azTS6hLEveLucrxxz7f4jZkQ9XRZssUpYV3ybAe1EBB3pRaRw+jIrA9ZrlbpPLYTlXe6y0Bfjj4N1yPbXfgGhVmV8FhlBzFtejlJ25QoU/TiVU+OMsc5j9qrrdz+ww+6tKHmBH8Ax+ADW/7mcCGd65WuUCPgccBG5HBbt4NXCC2ijSK1omlHJV6teOozwrNhOk1bgY9UdFEDwa7Ls+ONYwly7M/rwyoaZC/T1q0HIrte+M6iiTnwza9kZgC/CvzB2S/hvB9huDY16qMPsLttMc5Z9j7jD7yybThQj9jkCQkoZ4TdW2+4H768rLOZbnqrb/AWpEaAo1SfKrwM4letAWLUvwey5Z6uW9C/gJ6oP9FFWdoNUixypqk/ei/NjHUC/EHwb7G8vdJpdCluVql/ORY459P0SdUrNa2mQxsqyGNgH+Myrs+wQqB9E3gdtWSptcDstC7bHSFuZ+/0vgQ1VlRHC/H0EFvnkAWF93nBRqPspwsPw5kFxu+YK63U+tgrYq5UEpMj8K6vw0al6rqNq+quRCRQz9w+CdOYEKgPI7QGi1yEQlbUn98rmLWX+UVfjB4BhHUIOBlyTE/kIyoRTp+d4Z91Qdw0XlgDyFUoi+QlX4+aBMOyrVwnhQ7uOAuxztNEf555itoC2rTCI4gUaj0Wg0Go1Go9FolpnzCRKi0Wg0Go1Go9FoNJpLiFbQNBqNRqPRaDQajWaFoBU0jUaj0Wg0Go1Go1khaAVNo9FoNBqNRqPRaFYIWkHTaDQajUaj0Wg0mhWCVtA0Go1Go9FoNBqNZoWgFTSNRqPRaDQajUajWSFoBU2j0Wg0Go1Go9FoVghaQdNoNBqNRqPRaDSaFcL/B1UOGbbADi+4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x1008 with 14 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "with LV_model:\n",
    "    pm.traceplot(trace);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/demetri/Documents/GitHub/pymc3/pymc3/stats.py:991: FutureWarning: The join_axes-keyword is deprecated. Use .reindex or .reindex_like on the result to achieve the same functionality.\n",
      "  axis=1, join_axes=[dforg.index])\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>sd</th>\n",
       "      <th>mc_error</th>\n",
       "      <th>hpd_2.5</th>\n",
       "      <th>hpd_97.5</th>\n",
       "      <th>n_eff</th>\n",
       "      <th>Rhat</th>\n",
       "      <th>STAN_mus</th>\n",
       "      <th>STAN_sds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>alpha</th>\n",
       "      <td>0.547585</td>\n",
       "      <td>0.063396</td>\n",
       "      <td>0.001855</td>\n",
       "      <td>0.424077</td>\n",
       "      <td>0.667619</td>\n",
       "      <td>1129.131061</td>\n",
       "      <td>0.999675</td>\n",
       "      <td>0.549</td>\n",
       "      <td>0.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta</th>\n",
       "      <td>0.027791</td>\n",
       "      <td>0.004173</td>\n",
       "      <td>0.000120</td>\n",
       "      <td>0.019770</td>\n",
       "      <td>0.035841</td>\n",
       "      <td>1234.460403</td>\n",
       "      <td>0.999681</td>\n",
       "      <td>0.028</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gamma</th>\n",
       "      <td>0.799312</td>\n",
       "      <td>0.089968</td>\n",
       "      <td>0.002709</td>\n",
       "      <td>0.631930</td>\n",
       "      <td>0.979657</td>\n",
       "      <td>1058.220941</td>\n",
       "      <td>0.999788</td>\n",
       "      <td>0.797</td>\n",
       "      <td>0.091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>delta</th>\n",
       "      <td>0.024073</td>\n",
       "      <td>0.003527</td>\n",
       "      <td>0.000106</td>\n",
       "      <td>0.017160</td>\n",
       "      <td>0.030609</td>\n",
       "      <td>1082.070068</td>\n",
       "      <td>0.999801</td>\n",
       "      <td>0.024</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>xto</th>\n",
       "      <td>34.013033</td>\n",
       "      <td>2.991276</td>\n",
       "      <td>0.061384</td>\n",
       "      <td>28.734277</td>\n",
       "      <td>40.500802</td>\n",
       "      <td>2040.864990</td>\n",
       "      <td>0.999835</td>\n",
       "      <td>33.960</td>\n",
       "      <td>2.909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yto</th>\n",
       "      <td>5.940363</td>\n",
       "      <td>0.540310</td>\n",
       "      <td>0.011514</td>\n",
       "      <td>4.895678</td>\n",
       "      <td>7.009835</td>\n",
       "      <td>1802.717906</td>\n",
       "      <td>1.001373</td>\n",
       "      <td>5.949</td>\n",
       "      <td>0.533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sigma__0</th>\n",
       "      <td>0.248527</td>\n",
       "      <td>0.044718</td>\n",
       "      <td>0.001088</td>\n",
       "      <td>0.174826</td>\n",
       "      <td>0.338598</td>\n",
       "      <td>1567.059938</td>\n",
       "      <td>0.999854</td>\n",
       "      <td>0.248</td>\n",
       "      <td>0.045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sigma__1</th>\n",
       "      <td>0.251432</td>\n",
       "      <td>0.042835</td>\n",
       "      <td>0.000853</td>\n",
       "      <td>0.174449</td>\n",
       "      <td>0.335463</td>\n",
       "      <td>2130.267462</td>\n",
       "      <td>1.000443</td>\n",
       "      <td>0.252</td>\n",
       "      <td>0.044</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               mean        sd  mc_error    hpd_2.5   hpd_97.5        n_eff  \\\n",
       "alpha      0.547585  0.063396  0.001855   0.424077   0.667619  1129.131061   \n",
       "beta       0.027791  0.004173  0.000120   0.019770   0.035841  1234.460403   \n",
       "gamma      0.799312  0.089968  0.002709   0.631930   0.979657  1058.220941   \n",
       "delta      0.024073  0.003527  0.000106   0.017160   0.030609  1082.070068   \n",
       "xto       34.013033  2.991276  0.061384  28.734277  40.500802  2040.864990   \n",
       "yto        5.940363  0.540310  0.011514   4.895678   7.009835  1802.717906   \n",
       "sigma__0   0.248527  0.044718  0.001088   0.174826   0.338598  1567.059938   \n",
       "sigma__1   0.251432  0.042835  0.000853   0.174449   0.335463  2130.267462   \n",
       "\n",
       "              Rhat  STAN_mus  STAN_sds  \n",
       "alpha     0.999675     0.549     0.065  \n",
       "beta      0.999681     0.028     0.004  \n",
       "gamma     0.999788     0.797     0.091  \n",
       "delta     0.999801     0.024     0.004  \n",
       "xto       0.999835    33.960     2.909  \n",
       "yto       1.001373     5.949     0.533  \n",
       "sigma__0  0.999854     0.248     0.045  \n",
       "sigma__1  1.000443     0.252     0.044  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "summary = pm.summary(trace)\n",
    "STAN_mus = [0.549, 0.028, 0.797, 0.024, 33.960, 5.949, 0.248, 0.252]\n",
    "STAN_sds = [0.065, 0.004, 0.091, 0.004, 2.909, 0.533, 0.045, 0.044]\n",
    "summary['STAN_mus'] = pd.Series(np.array(STAN_mus), index=summary.index)\n",
    "summary['STAN_sds'] = pd.Series(np.array(STAN_sds), index=summary.index)\n",
    "summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These estimates are almost identical to those obtained in the Stan tutorial (see the last two columns above), which is what we can expect. Posterior predictives can be drawn as below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/demetri/Documents/GitHub/pymc3/pymc3/sampling.py:1078: UserWarning: samples parameter is smaller than nchains times ndraws, some draws and/or chains may not be represented in the returned posterior predictive sample\n",
      "  warnings.warn(\"samples parameter is smaller than nchains times ndraws, some draws \"\n",
      "100%|██████████| 1000/1000 [00:10<00:00, 98.26it/s]\n"
     ]
    }
   ],
   "source": [
    "ppc_samples = pm.sample_posterior_predictive(trace, samples=1000, model=LV_model)['Y_obs']\n",
    "mean_ppc = ppc_samples.mean(axis=0)\n",
    "CriL_ppc = np.percentile(ppc_samples,q=2.5,axis=0)\n",
    "CriU_ppc = np.percentile(ppc_samples,q=97.5,axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 2*(5)))\n",
    "plt.subplot(2,1,1)\n",
    "plt.plot(Year,Lynx,'o', color='b', lw=4, ms=10.5)\n",
    "plt.plot(Year,mean_ppc[:,1], color='b', lw=4)\n",
    "plt.plot(Year,CriL_ppc[:,1], '--', color='b', lw=2)\n",
    "plt.plot(Year,CriU_ppc[:,1], '--',  color='b', lw=2)\n",
    "plt.xlim([1900,1920])\n",
    "plt.ylabel('Lynx conc', fontsize=15)\n",
    "plt.xticks(Year,rotation=45);\n",
    "plt.subplot(2,1,2)\n",
    "plt.plot(Year,Hare,'o', color='g', lw=4, ms=10.5, label='Observed')\n",
    "plt.plot(Year,mean_ppc[:,0], color='g', lw=4, label='mean of ppc')\n",
    "plt.plot(Year,CriL_ppc[:,0], '--',  color='g', lw=2, label='credible intervals')\n",
    "plt.plot(Year,CriU_ppc[:,0], '--',  color='g', lw=2)\n",
    "plt.legend(fontsize=15)\n",
    "plt.xlim([1900,1920])\n",
    "plt.xlabel('Year', fontsize=15)\n",
    "plt.ylabel('Hare conc', fontsize=15)\n",
    "plt.xticks(Year,rotation=45);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Efficient exploration of the posterior landscape with SMC\n",
    "\n",
    "It has been pointed out in several papers that the complex non-linear dynamics of an ODE results in a posterior landscape that is extremely difficult to navigate efficiently by many MCMC samplers. Thus, recently the curvature information of the posterior surface has been used to construct powerful geometrically aware samplers ([Mark Girolami and Ben Calderhead, 2011](https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/j.1467-9868.2010.00765.x)) that perform extremely well in ODE inference problems. Another set of ideas suggest breaking down a complex inference task into a sequence of simpler tasks. In essence the idea is to use sequential-importance-sampling to sample from an artificial sequence of increasingly complex distributions where the first in the sequence is a distribution that is easy to sample from, the prior, and the last in the sequence is the actual complex target distribution. The associated importance distribution is constructed by moving the set of particles sampled at the previous step using a Markov kernel, say for example the MH kernel. \n",
    "\n",
    "A simple way of building the sequence of distributions is to use a temperature $\\beta$, that is raised slowly from $0$ to $1$. Using this temperature variable $\\beta$ we can write down the annealed intermediate distribution as\n",
    "\n",
    "$$p_{\\beta}(\\boldsymbol{\\theta}|\\boldsymbol{y})\\propto p(\\boldsymbol{y}|\\boldsymbol{\\theta})^{\\beta} p(\\boldsymbol{\\theta}).$$\n",
    "\n",
    "Samplers that carry out sequential-importance-sampling from these artificial sequence of distributions, to avoid the difficult task of sampling directly from $p(\\boldsymbol{\\theta}|\\boldsymbol{y})$, are known as Sequential Monte Carlo (SMC) samplers ([P Del Moral et al., 2006](https://rss.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-9868.2006.00553.x)). The performance of these samplers are sensitive to the choice of the temperature schedule, that is the set of user-defined increasing values of $\\beta$ between $0$ and $1$. Fortunately, PyMC3 provides a version of the SMC sampler ([Jianye Ching and Yi-Chu Chen, 2007](https://ascelibrary.org/doi/10.1061/%28ASCE%290733-9399%282007%29133%3A7%28816%29)) that automatically figures out this temperature schedule. Moreover, the PyMC3's SMC sampler does not require the gradient of the log target density. As a result it is extremely easy to use this sampler for inference in ODE models. In the next example I will apply this SMC sampler to estimate the parameters of the Fitzhugh-Nagumo model. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Fitzhugh-Nagumo model\n",
    "\n",
    "The Fitzhugh-Nagumo model given by\n",
    "$$\n",
    "\\begin{aligned}\n",
    "\\frac{dV}{dt}&=(V - \\frac{V^3}{3} + R)c\\\\\n",
    "\\frac{dR}{dt}&=\\frac{-(V-a+bR)}{c},\n",
    "\\end{aligned}\n",
    "$$\n",
    "consisting of a membrane voltage variable $V(t)$ and a recovery variable $R(t)$ is a two-dimensional simplification of the [Hodgkin-Huxley](http://www.scholarpedia.org/article/Conductance-based_models) model of spike (action potential) generation in squid giant axons and where $a$, $b$, $c$ are the model parameters. This model produces a rich dynamics and as a result a complex geometry of the posterior surface that often leads to poor performance of many MCMC samplers. As a result this model was used to test the efficacy of the discussed geometric MCMC scheme and since then has been used to benchmark other novel MCMC methods. Following [Mark Girolami and Ben Calderhead, 2011](https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/j.1467-9868.2010.00765.x) I will also use artificially generated data from this model to setup the inference task for estimating $\\boldsymbol{\\theta}=(a,b,c)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "class FitzhughNagumoModel(object):\n",
    "    def __init__(self, times, y0=None):\n",
    "            self._y0 = np.array([-1, 1], dtype=np.float64)\n",
    "            self._times = times\n",
    "           \n",
    "    def _simulate(self, parameters, times):\n",
    "        a, b, c = [float(x) for x in parameters]\n",
    "\n",
    "        def rhs(y, t, p):\n",
    "            V, R = y\n",
    "            dV_dt = (V - V**3 / 3 + R) * c\n",
    "            dR_dt = (V - a + b * R) / -c\n",
    "            return dV_dt, dR_dt\n",
    "        values = odeint(rhs, self._y0, times, (parameters,),rtol=1e-6,atol=1e-6)\n",
    "        return values\n",
    "    \n",
    "    def simulate(self, x):\n",
    "        return self._simulate(x, self._times)\n",
    "      "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulated Data\n",
    "\n",
    "For this example I am going to use simulated data that is I will generate noisy traces from the forward model defined above with parameters $\\theta$ set to $(0.2,0.2,3)$ respectively and corrupted by i.i.d Gaussian noise with a standard deviation $\\sigma=0.5$. The initial values are set to $V(0)=-1$ and $R(0)=1$ respectively. Again following [Mark Girolami and Ben Calderhead, 2011](https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/j.1467-9868.2010.00765.x) I will assume that the initial values are known. These parameter values pushes the model into the oscillatory regime."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x540 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_states = 2\n",
    "n_times = 200\n",
    "true_params = [0.2,0.2,3.]\n",
    "noise_sigma = 0.5\n",
    "FN_solver_times = np.linspace(0, 20, n_times)\n",
    "ode_model = FitzhughNagumoModel(FN_solver_times)\n",
    "sim_data = ode_model.simulate(true_params)  \n",
    "np.random.seed(42)\n",
    "Y_sim = sim_data + np.random.randn(n_times,n_states)*noise_sigma\n",
    "plt.figure(figsize=(15, 7.5))\n",
    "plt.plot(FN_solver_times, sim_data[:,0], color='darkblue', lw=4, label=r'$V(t)$')\n",
    "plt.plot(FN_solver_times, sim_data[:,1], color='darkgreen', lw=4, label=r'$R(t)$')\n",
    "plt.plot(FN_solver_times, Y_sim[:,0], 'o', color='darkblue', ms=4.5, label='Noisy traces')\n",
    "plt.plot(FN_solver_times, Y_sim[:,1], 'o', color='darkgreen', ms=4.5)\n",
    "plt.legend(fontsize=15)\n",
    "plt.xlabel('Time',fontsize=15)\n",
    "plt.ylabel('Values',fontsize=15)\n",
    "plt.title('Fitzhugh-Nagumo Action Potential Model', fontsize=25);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Define a non-differentiable black-box op using Theano @as_op\n",
    "\n",
    "Remember that I told SMC sampler does not require gradients, this is by the way the case for other samplers such as the Metropolis-Hastings, Slice sampler that are also supported in PyMC3. For all these gradient-free samplers I will show a simple and quick way of wrapping the forward model i.e. the ODE solution in Theano. All we have to do is to simply to use the decorator `as_op` that converts a python function into a basic Theano Op. We also tell Theano using the `as_op` decorator that we have three parameters each being a Theano scalar. The output then is a Theano matrix whose columns are the state vectors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import theano.tensor as tt\n",
    "from theano.compile.ops import as_op\n",
    "\n",
    "@as_op(itypes=[tt.dscalar,tt.dscalar,tt.dscalar], otypes=[tt.dmatrix])\n",
    "def th_forward_model(param1,param2,param3):\n",
    "    \n",
    "    param = [param1,param2,param3]\n",
    "    th_states = ode_model.simulate(param)\n",
    "    \n",
    "    return th_states"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generative model\n",
    "\n",
    "Since I have corrupted the original traces with i.i.d Gaussian thus the likelihood is given by\n",
    "$$\\boldsymbol{Y} = \\prod_{i=1}^T \\mathcal{N}(\\boldsymbol{X}(t_i)), \\sigma^2\\mathbb{I}),$$ \n",
    "where $\\mathbb{I}\\in \\mathbb{R}^{K \\times K}$. We place a Gamma, Normal, Uniform prior on $(a,b,c)$ and a HalfNormal prior on $\\sigma$ as follows:\n",
    "$$\n",
    "\\begin{aligned}\n",
    "\ta & \\sim \\mathcal{Gamma}(2,1),\\\\\n",
    "\tb & \\sim \\mathcal{N}(0,1),\\\\\n",
    "\tc & \\sim \\mathcal{U}(0.1,1),\\\\\n",
    "\t\\sigma & \\sim \\mathcal{H}(1).\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "Notice how I have used the `start` argument for this example. Just like `pm.sample` `pm.sample_smc` has a number of settings, but I found the default ones good enough for simple models such as this one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sample initial stage: ...\n",
      "Stage: 0 Beta: 0.009 Steps: 25\n",
      "Stage: 1 Beta: 0.015 Steps: 8\n",
      "Stage: 2 Beta: 0.020 Steps: 4\n",
      "Stage: 3 Beta: 0.030 Steps: 13\n",
      "Stage: 4 Beta: 0.049 Steps: 3\n",
      "Stage: 5 Beta: 0.089 Steps: 10\n",
      "Stage: 6 Beta: 0.178 Steps: 3\n",
      "Stage: 7 Beta: 0.368 Steps: 8\n",
      "Stage: 8 Beta: 0.782 Steps: 3\n",
      "Stage: 9 Beta: 1.000 Steps: 7\n"
     ]
    }
   ],
   "source": [
    "draws = 1000\n",
    "with pm.Model() as FN_model:\n",
    "\n",
    "    a = pm.Gamma('a', alpha=2, beta=1)\n",
    "    b = pm.Normal('b', mu=0, sd=1)\n",
    "    c = pm.Uniform('c', lower=0.1, upper=10)\n",
    "    \n",
    "    sigma = pm.HalfNormal('sigma', sd=1)\n",
    "    \n",
    "    forward = th_forward_model(a,b,c)\n",
    "    \n",
    "    cov=np.eye(2)*sigma**2\n",
    "    \n",
    "    \n",
    "    Y_obs = pm.MvNormal('Y_obs', mu=forward, cov=cov, observed=Y_sim)\n",
    "\n",
    "    startsmc =  {v.name:np.random.uniform(1e-3,2, size=draws) for v in FN_model.free_RVs}\n",
    "\n",
    "    trace_FN = pm.sample_smc(draws, start=startsmc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pm.plot_posterior(trace_FN, kind='hist', bins=30, color='seagreen');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inference summary\n",
    "\n",
    "With `pm.SMC`, do I get similar performance to geometric MCMC samplers (see [Mark Girolami and Ben Calderhead, 2011](https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/j.1467-9868.2010.00765.x))? I think so !"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "results=[pm.summary(trace_FN, ['a']),pm.summary(trace_FN, ['b']),pm.summary(trace_FN, ['c'])\\\n",
    "        ,pm.summary(trace_FN, ['sigma'])]\n",
    "results=pd.concat(results)\n",
    "true_params.append(noise_sigma)\n",
    "results['True values'] = pd.Series(np.array(true_params), index=results.index)\n",
    "true_params.pop();\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reconstruction of the phase portrait\n",
    "\n",
    "Its good to check that we can reconstruct the (famous) pahse portrait for this model based on the obtained samples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "params=np.array([trace_FN.get_values('a'),trace_FN.get_values('b'),trace_FN.get_values('c')]).T\n",
    "params.shape\n",
    "new_values = []\n",
    "for ind in range(len(params)):\n",
    "    ppc_sol= ode_model.simulate(params[ind])\n",
    "    new_values.append(ppc_sol)\n",
    "new_values = np.array(new_values)\n",
    "mean_values = np.mean(new_values, axis=0)\n",
    "plt.figure(figsize=(15, 7.5))\n",
    "\n",
    "plt.plot(mean_values[:,0], mean_values[:,1], color='black', lw=4, label='Inferred (mean of sampled) phase portrait')\n",
    "plt.plot(sim_data[:,0], sim_data[:,1], '--', color='#ff7f0e', lw=4, ms=6, label='True phase portrait')\n",
    "plt.legend(fontsize=15)\n",
    "plt.xlabel(r'$V(t)$',fontsize=15)\n",
    "plt.ylabel(r'$R(t)$',fontsize=15);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Perspectives\n",
    "\n",
    "### Using some other ODE models\n",
    "\n",
    "I have tried to keep everything as general as possible. So, my custom ODE Op, the state and VSP evaluator as well as the cached solver are not tied to a specific ODE model. Thus, to use any other ODE model one only needs to implement a `simulate_with_sensitivities` method according to their own specific ODE model.\n",
    "\n",
    "### Other forms of differential equation (DDE, DAE, PDE)\n",
    "\n",
    "I hope the two examples have elucidated the applicability of PyMC3 in regards to fitting ODE models. Although ODEs are the most fundamental constituent of a mathematical model, there are indeed other forms of dynamical systems such as a delay differential equation (DDE), a differential algebraic equation (DAE) and the partial differential equation (PDE) whose parameter estimation is equally important. The SMC and for that matter any other non-gradient sampler supported by PyMC3 can be used to fit all these forms of differential equation, of course using the `as_op`. However, just like an ODE we can solve augmented systems of DDE/DAE along with their sensitivity equations. The sensitivity equations for a DDE and a DAE can be found in this recent paper, [C Rackauckas et al., 2018](https://arxiv.org/abs/1812.01892) (Equation 9 and 10). Thus we can easily apply NUTS sampler to these models.\n",
    "\n",
    "### Stan already supports ODEs\n",
    "\n",
    "Well there are many problems where I believe SMC sampler would be more suitable than NUTS and thus its good to have that option. \n",
    "\n",
    "### Model selection\n",
    "\n",
    "Most ODE inference literature since [Vladislav Vyshemirsky and Mark Girolami, 2008](https://academic.oup.com/bioinformatics/article/24/6/833/192524) recommend the usage of Bayes factor for the purpose of model selection/comparison. This involves the calculation of the marginal likelihood which is a much more nuanced topic and I would refrain from any discussion about that. Fortunately, the SMC sampler calculates the marginal likelihood as a by product so this can be used for obtaining Bayes factors. Follow PyMC3's other tutorials for further information regarding how to obtain the marginal likelihood after running the SMC sampler.\n",
    "\n",
    "Since we generally frame the ODE inference as a regression problem (along with the i.i.d measurement noise assumption in most cases) we can straight away use any of the supported information criterion, such as the widely available information criterion (WAIC), irrespective of what sampler is used for inference. See the PyMC3's API for further information regarding WAIC.\n",
    "\n",
    "###  Other AD packages\n",
    "\n",
    "Although this is a slight digression nonetheless I would still like to point out my observations on this issue. The approach that I have presented here for embedding an ODE (also extends to DDE/DAE) as a custom Op can be trivially carried forward to other AD packages such as TensorFlow and PyTorch. I had been able to use TensorFlow's [py_func](https://www.tensorflow.org/api_docs/python/tf/py_func) to build a custom TensorFlow ODE Op and then use that in the [Edward](http://edwardlib.org/) ppl. I would recommend [this](https://pytorch.org/tutorials/advanced/numpy_extensions_tutorial.html) tutorial, for writing PyTorch extensions, to those who are interested in using the [Pyro](http://pyro.ai/) ppl.\n",
    " \n",
    "\n"
   ]
  }
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